credit meaning in assignment

Credit Assignment

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Claude Sammut 3

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Claude Sammut

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Faculty of Information Technology, Monash University, Melbourne, VIC, Australia

Geoffrey I. Webb

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Sammut, C. (2017). Credit Assignment. In: Sammut, C., Webb, G.I. (eds) Encyclopedia of Machine Learning and Data Mining. Springer, Boston, MA. https://doi.org/10.1007/978-1-4899-7687-1_185

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MINI REVIEW article

Solving the credit assignment problem with the prefrontal cortex.

$\r\nAlexandra Stolyarova*$

Department of Psychology, University of California, Los Angeles, Los Angeles, CA, United States

In naturalistic multi-cue and multi-step learning tasks, where outcomes of behavior are delayed in time, discovering which choices are responsible for rewards can present a challenge, known as the credit assignment problem . In this review, I summarize recent work that highlighted a critical role for the prefrontal cortex (PFC) in assigning credit where it is due in tasks where only a few of the multitude of cues or choices are relevant to the final outcome of behavior. Collectively, these investigations have provided compelling support for specialized roles of the orbitofrontal (OFC), anterior cingulate (ACC), and dorsolateral prefrontal (dlPFC) cortices in contingent learning. However, recent work has similarly revealed shared contributions and emphasized rich and heterogeneous response properties of neurons in these brain regions. Such functional overlap is not surprising given the complexity of reciprocal projections spanning the PFC. In the concluding section, I overview the evidence suggesting that the OFC, ACC and dlPFC communicate extensively, sharing the information about presented options, executed decisions and received rewards, which enables them to assign credit for outcomes to choices on which they are contingent. This account suggests that lesion or inactivation/inhibition experiments targeting a localized PFC subregion will be insufficient to gain a fine-grained understanding of credit assignment during learning and instead poses refined questions for future research, shifting the focus from focal manipulations to experimental techniques targeting cortico-cortical projections.

Introduction

When an animal is introduced to an unfamiliar environment, it will explore the surroundings randomly until an unexpected reward is encountered. Reinforced by this experience, the animal will gradually learn to repeat those actions that produced the desired outcome. The work conducted in the past several decades has contributed a detailed understanding of the psychological and neural mechanisms that support such reinforcement-driven learning ( Schultz and Dickinson, 2000 ; Schultz, 2004 ; Niv, 2009 ). It is now broadly accepted that dopamine (DA) signaling conveys prediction errors, or the degree of surprise brought about by unexpected rewards, and interacts with cortical and basal ganglia circuits to selectively reinforce the advantageous choices ( Schultz, 1998a , b ; Schultz and Dickinson, 2000 ; Niv, 2009 ). Yet, in naturalistic settings, where rewards are delayed in time, and where multiple cues are encountered, or where several decisions are made before the outcomes of behavior are revealed, discovering which choices are responsible for rewards can present a challenge, known as the credit assignment problem ( Mackintosh, 1975 ; Rothkopf and Ballard, 2010 ).

In most everyday situations, the rewards are not immediate consequences of behavior, but instead appear after substantial delays. To influence future choices, the teaching signal conveyed by DA release needs to reinforce synaptic events occurring on a millisecond timescale, frequently seconds before the outcomes of decisions are revealed ( Izhikevich, 2007 ; Fisher et al., 2017 ). This apparent difficulty in linking preceding behaviors caused by transient neuronal activity to a delayed feedback has been termed the distal reward or temporal credit assignment problem ( Hull, 1943 ; Barto et al., 1983 ; Sutton and Barto, 1998 ; Dayan and Abbott, 2001 ; Wörgötter and Porr, 2005 ). Credit for the reward delayed by several seconds can frequently be assigned by establishing an eligibility trace, a molecular memory of the recent neuronal activity, allowing modification of synaptic connections that participated in the behavior ( Pan et al., 2005 ; Fisher et al., 2017 ). On longer timescales, or when multiple actions need to be performed sequentially to reach a final goal, intermediate steps themselves can acquire motivational significance and subsequently reinforce preceding decisions, such as in temporal-difference (TD) learning models ( Sutton and Barto, 1998 ).

Several excellent reviews have summarized the accumulated knowledge on mechanisms that link choices and their outcomes through time, highlighting the advantages of eligibility traces and TD models ( Wörgötter and Porr, 2005 ; Barto, 2007 ; Niv, 2009 ; Walsh and Anderson, 2014 ). Yet these solutions to the distal reward problem can impede learning in multi-choice tasks, or when an animal is presented with many irrelevant stimuli prior to or during the delay. Here, I only briefly overview the work on the distal reward problem to highlight potential complications that can arise in credit assignment based on eligibility traces when learning in multi-cue environments. Instead, I focus on the structural (or spatial ) credit assignment problem, requiring animals to select and learn about the most meaningful features in the environment and ignore irrelevant distractors. Collectively, the reviewed evidence highlights a critical role for the prefrontal cortex (PFC) in such contingent learning.

Recent studies have provided compelling support for specialized functions of the orbitofrontal (OFC) and dorsolateral prefrontal (dlPFC) cortices in credit assignment in multi-cue tasks, with fewer experiments targeting the anterior cingulate cortex (ACC). For example, it has seen suggested that the dlPFC aids reinforcement-driven learning by directing attention to task-relevant cues ( Niv et al., 2015 ), the OFC assigns credit for rewards based on the causal relationship between trial outcomes and choices ( Jocham et al., 2016 ; Noonan et al., 2017 ), whereas the ACC contributes to unlearning of action-outcome associations when the rewards are available for free ( Jackson et al., 2016 ). However, this work has similarly revealed shared contributions and emphasized rich and heterogeneous response properties of neurons in the PFC, with different subregions monitoring and integrating the information about the task (i.e., current context, available options, anticipated rewards, as well as delay and effort costs) at variable times within a trial (upon stimulus presentation, action selection, outcome anticipation, and feedback monitoring; ex., Hunt et al., 2015 ; Khamassi et al., 2015 ). In the concluding section, I overview the evidence suggesting that contingent learning in multi-cue environments relies on dynamic cortico-cortical interactions during decision making and outcome valuation.

Solving the Temporal Credit Assignment Problem

When outcomes follow choices after short delays (Figure 1A ), the credit for distal rewards can frequently be assigned by establishing an eligibility trace, a sustained memory of the recent activity that renders synaptic connections malleable to modification over several seconds. Eligibility traces can persist as elevated levels of calcium in dendritic spines of post-synaptic neurons ( Kötter and Wickens, 1995 ) or as a sustained neuronal activity throughout the delay period ( Curtis and Lee, 2010 ) to allow for synaptic changes in response to reward signals. Furthermore, spike-timing dependent plasticity can be influenced by neuromodulator input ( Izhikevich, 2007 ; Abraham, 2008 ; Fisher et al., 2017 ). For example, the magnitude of short-term plasticity can be modulated by DA, acetylcholine and noradrenaline, which may even revert the sign of the synaptic change ( Matsuda et al., 2006 ; Izhikevich, 2007 ; Seol et al., 2007 ; Abraham, 2008 ; Zhang et al., 2009 ). Sustained neural activity has been observed in the PFC and striatum ( Jog et al., 1999 ; Pasupathy and Miller, 2005 ; Histed et al., 2009 ; Kim et al., 2009 , 2013 ; Seo et al., 2012 ; Her et al., 2016 ), as well as the sensory cortices after experience with consistent pairings between the stimuli and outcomes separated by predictable delays ( Shuler and Bear, 2006 ).

Figure 1 . Example tasks highlighting the challenge of credit assignment and learning strategies enabling animals to solve this problem. (A) An example of a distal reward task that can be successfully learned with eligibility traces and TD rules, where intermediate choices can acquire motivational significance and subsequently reinforce preceding decisions (ex., Pasupathy and Miller, 2005 ; Histed et al., 2009 ). (B) In this version of the task, multiple cues are present at the time of choice, only one of which is meaningful for obtaining rewards. After a brief presentation, the stimuli disappear, requiring an animal to solve a complex structural and temporal credit assignment problem (ex., Noonan et al., 2010 , 2017 ; Niv et al., 2015 ; Asaad et al., 2017 ; while the schematic of the task captures the challenge of credit assignment, note that in some experimental variants of the behavioral paradigm stimuli disappeared before an animal revealed its choice, whereas in others the cues remained on the screen until the trial outcome was revealed). Under such conditions, learning based on eligibility traces is suboptimal, as non-specific reward signals can reinforce visual cues that did not meaningfully contribute, but occurred close, to beneficial outcomes of behavior. (C) On reward tasks, similar to the one shown in (B) , the impact of previous decisions and associated rewards on current behavior can be assessed by performing regression analyses ( Jocham et al., 2016 ; Noonan et al., 2017 ). Here, the color of each cell in a matrix represents the magnitude of the effect of short-term choice and outcome histories, up to 4 trials into the past (red-strong influence; blue-weak influence on the current decision). Top: an animal learning based on the causal relationship between outcomes and choices (i.e., contingent learning). Middle: each choice is reinforced by a combined history of rewards (i.e., decisions are repeated if beneficial outcomes occur frequently). Bottom: the influence of recent rewards spreads to unrelated choices.

On extended timescales, when multiple actions need to be performed sequentially to reach a final goal, the distal reward problem can be solved by assigning motivational significance to intermediate choices that can subsequently reinforce preceding decisions, such as in TD learning models ( Montague et al., 1996 ; Sutton and Barto, 1998 ; Barto, 2007 ). Assigning values to these intervening steps according to expected future rewards allows to break complex temporal credit assignment problems into smaller and easier tasks. There is ample evidence for TD learning in humans and other animals that on the neural level is supported by transfer of DA responses from the time of reward delivery to preceding cues and actions ( Montague et al., 1996 ; Schultz, 1998a , b ; Walsh and Anderson, 2014 ).

Both TD learning and eligibility traces offer elegant solutions to the distal reward problem, and models based on cooperation between these two mechanisms can predict animal behavior as well as neuronal responses to rewards and predictive stimuli ( Pan et al., 2005 ; Bogacz et al., 2007 ). Yet assigning credit based on eligibility traces can be suboptimal when an animal interacts with many irrelevant stimuli prior to or during the delay (Figure 1B ). Under such conditions sensory areas remain responsive to distracting stimuli and the arrival of non-specific reward signals can reinforce intervening cues that did not meaningfully contribute, but occurred close, to the outcome of behavior ( FitzGerald et al., 2013 ; Xu, 2017 ).

The Role of the PFC in Structural Credit Assignment

Several recent studies have investigated the neural mechanisms of appropriate credit assignment in challenging tasks where only a few of the multitude of cues predict rewards reliably. Collectively, this work has provided compelling support for causal contributions of the PFC to structural credit assignment. For example, Asaad et al. (2017) examined the activity of neurons in monkey dlPFC while subjects were performing a delayed learning task. The arrangement of the stimuli varied randomly between trials and within each block either the spatial location or stimulus identity was relevant for solving the task. The monkeys' goal was to learn by trial-and-error to select one of the four options that led to rewards according to current rules. When stimulus identity was relevant for solving the task, neural activity in the dlPFC at the time of feedback reflected both the relevant cue (regardless of its spatial location) and the trial outcome, thus integrating the information necessary for credit assignment. Such responses were strategy-selective: these neurons did not encode cue identity at the time of feedback when it was not necessary for learning in the spatial location task, in which making a saccade to the same position on the screen was reinforced within a block of trials. Previous research has similarly indicated that neurons in the dlPFC respond selectively to behaviorally-relevant and attended stimuli ( Lebedev et al., 2004 ; Markowitz et al., 2015 ) and integrate information about prediction errors, choice values as well as outcome uncertainty prior to trial feedback ( Khamassi et al., 2015 ).

The activity within the dlPFC has been linked to structural credit assignment through selective attention and representational learning ( Niv et al., 2015 ). Under conditions of reward uncertainty and unknown relevant task features, human participants opt for computational efficiency and engage in a serial-hypothesis-testing strategy ( Wilson and Niv, 2011 ), selecting one cue and its anticipated outcome as the main focus of their behavior, and updating the expectations associated exclusively with that choice upon feedback receipt ( Akaishi et al., 2016 ). Niv and colleagues tested participant on a three-armed bandit task, where relevant stimulus dimensions (i.e., shape, color or texture) predicting outcome probabilities changed between block of trials ( Niv et al., 2015 ). In such multidimensional environment, reinforcement-driven learning was aided by attentional control mechanisms that engaged the dlPFC, intraparietal cortex, and precuneus.

In many tasks, the credit for outcomes can be assigned according to different rules: based on the causal relationship between rewards and choices (i.e., contingent learning), their temporal proximity (i.e., when the reward is received shortly after a response), or their statistical relationship (when an action has been executed frequently before beneficial outcomes; Jocham et al., 2016 ; Figure 1C ). The analyses presented in papers discussed above did not allow for the dissociation between these alternative strategies of credit assignment. By testing human participants on a task with continuous stimulus presentation, instead of a typical trial-by-trial structure, Jocham et al. (2016) demonstrated that the tendency to repeat choices that were immediately followed by rewards and causal learning operate in parallel. In this experiment, activity within another subregion of the PFC, the OFC, was associated with contingent learning. Complementary work in monkeys revealed that the OFC contributes causally to credit assignment ( Noonan et al., 2010 ): animals with OFC lesions were unable to associate a reward with the choice on which it was contingent and instead relied on temporal and statistical learning rules. In another recent paper, Noonan and colleagues (2017) extended these observations to humans, demonstrating causal contributions of the OFC to credit assignment across species. The participants were tested on a three-choice probabilistic learning task. The three options were presented simultaneously and maintained on the screen until the outcome of a decision was revealed, thus requiring participants to ignore irrelevant distractors. Notably, only patients with lateral OFC lesions displayed any difficulty in learning the task, whereas damage to the medial OFC or dorsomedial PFC preserved contingent learning mechanisms. However, it is presently unknown whether lesions to the dlPFC or ACC affect such causal learning.

In another test of credit assignment in learning, contingency degradation, the subjects are required to track causal relationships between the stimuli or actions and rewards. During contingency degradation sessions, the animals are still reinforced for responses, but rewards are also available for free. After experiencing non-contingent rewards, control subjects reliably decrease their choices of the stimuli. However, lesions to both the ACC and OFC inhibit contingency degradation ( Jackson et al., 2016 ). Taken together, these observations demonstrate causal contributions of the PFC to appropriate credit assignment in multi-cue environments.

Cooperation Between PFC Subregions Supports Contingent Learning in Multi-Cue Tasks

Despite the segregation of temporal and structural aspects of credit assignment in earlier sections of this review, in naturalistic settings the brains frequently need to tackle both problems simultaneously. Here, I overview the evidence favoring a network perspective, suggesting that dynamic cortico-cortical interactions during decision making and outcome valuation enable adaptive solutions to complex spatio-temporal credit assignment problems. It has been previously suggested that feedback projections from cortical areas occupying higher levels of processing hierarchy, including the PFC, can aid in attribution of outcomes to individual decisions by implementing attention-gated reinforcement learning ( Roelfsema and van Ooyen, 2005 ). Similarly, recent theoretical work has shown that even complex multi-cue and multi-step problems can be solved by an extended cascade model of synaptic memory traces, in which the plasticity is modulated not only by the activity within a population of neurons, but also by feedback about executed decisions and resulting rewards ( Urbanczik and Senn, 2009 ; Friedrich et al., 2010 , 2011 ). Contingent learning, according to these models, can be supported by the communication between neurons encoding available options, committed choices and outcomes of behavior during decision making and feedback monitoring. For example, at the time of outcome valuation, information about recent choices can be maintained as a memory trace in the neuronal population involved in action selection or conveyed by an efference copy from an interconnected brain region ( Curtis and Lee, 2010 ; Khamassi et al., 2011 , 2015 ). Similarly, reinforcement feedback is likely communicated as a global reward signal (ex., DA release) as well as projections from neural populations engaged in performance monitoring, such as those within the ACC ( Friedrich et al., 2010 ; Khamassi et al., 2011 ). The complexity of reciprocal and recurrent projections spanning the PFC ( Barbas and Pandya, 1989 ; Felleman and Van Essen, 1991 ; Elston, 2000 ) may enable this network to implement such learning rules, integrating the information about the task, executed decisions and performance feedback.

In many everyday decisions, the options are compared across multiple features simultaneously (ex., by considering current context, needs, available reward types, as well as delay and effort costs). Neurons in different subregions of the PFC exhibit rich response properties, signaling these features of the task at various time epochs within a trial. For example, reward selectivity in response to predictive stimuli emerges earlier in the OFC and may then be passed to the dlPFC that encodes both the expected outcome and the upcoming choice ( Wallis and Miller, 2003 ). Similarly, on trials where options are compared based on delays to rewards, choices are dependent on interactions between the OFC and dlPFC ( Hunt et al., 2015 ). Conversely, when effort costs are more meaningful for decisions, it is the ACC that influences choice-related activity in the dlPFC ( Hunt et al., 2015 ). The OFC is required not only for the evaluation of stimuli, but also more complex abstract rules, based on rewards they predict ( Buckley et al., 2009 ). While both the OFC and dlPFC encode abstract strategies (ex., persisting with recent choices or shifting to a new response), such signals appear earlier in the OFC and may be subsequently conveyed to the dlPFC where they are combined with upcoming response (i.e., left vs. right saccade) encoding ( Tsujimoto et al., 2011 ). Therefore, the OFC may be the first PFC subregion to encode task rules and/or potential rewards predicted by sensory cues; via cortico-cortical projections, this information may be subsequently communicated to the dlPFC or ACC ( Kennerley et al., 2009 ; Hayden and Platt, 2010 ) to drive strategy-sensitive response planning.

The behavioral strategy that the animal follows is influenced by recent reward history ( Cohen et al., 2007 ; Pearson et al., 2009 ). If its choices are reinforced frequently, the animal will make similar decisions in the future (i.e., exploit its current knowledge). Conversely, unexpected omission of expected rewards can signal a need for novel behaviors (i.e., exploration). Neurons in the dlPFC carry representations of planned as well as previous choices, anticipate outcomes, and jointly encode the current decisions and their consequences following feedback ( Seo and Lee, 2007 ; Seo et al., 2007 ; Tsujimoto et al., 2009 ; Asaad et al., 2017 ). Similarly, the ACC tracks trial-by-trial outcomes of decisions ( Procyk et al., 2000 ; Shidara and Richmond, 2002 ; Amiez et al., 2006 ; Quilodran et al., 2008 ) as well as reward and choice history ( Seo and Lee, 2007 ; Kennerley et al., 2009 , 2011 ; Sul et al., 2010 ; Kawai et al., 2015 ) and signals errors in outcome prediction ( Kennerley et al., 2009 , 2011 ; Hayden et al., 2011 ; Monosov, 2017 ). At the time of feedback, neurons in the OFC encode committed choices, their values and contingent rewards ( Tsujimoto et al., 2009 ; Sul et al., 2010 ). Notably, while the OFC encodes the identity of expected outcomes and the value of the chosen option after the alternatives are presented to an animal, it does not appear to encode upcoming decisions ( Tremblay and Schultz, 1999 ; Wallis and Miller, 2003 ; Padoa-Schioppa and Assad, 2006 ; Sul et al., 2010 ; McDannald et al., 2014 ), therefore it might be that feedback projections from the dlPFC or ACC are required for such activity to emerge at the time of reward feedback.

To capture the interactions between PFC subregions in reinforcement-driven learning, Khamassi and colleagues have formulated a computation model in which action values are stored and updated in the ACC and then communicated to the dlPFC that decides which action to trigger ( Khamassi et al., 2011 , 2013 ). This model relies on meta-learning principles ( Doya, 2002 ), flexibly adjusting the exploration-exploitation parameter based on performance history and variability in the environment that are monitored by the ACC. The explore-exploit parameter then influences action-selection mechanisms in the dlPFC, prioritizing choice repetition once the rewarded actions are discovered and encouraging switching between different options when environmental conditions change. In addition to highlighting the dynamic interactions between the dlPFC and ACC in learning, the model similarly offers an elegant solution to the credit assignment problem by restricting value updating only to those actions that were selected on a given trial. This is implemented by requiring the prediction error signals in the ACC to coincide with a motor efference copy sent by the premotor cortex. The model is endorsed with an ability to learn meta-values of novel objects in the environment based on the changes in the average reward that follow the presentation of such stimuli. While the authors proposed that such meta-value learning is implemented by the ACC, it is plausible that the OFC also plays a role in this process based on its contributions to stimulus-outcome and state learning ( Wilson et al., 2014 ; Zsuga et al., 2016 ). Intriguingly, this model could reproduce monkey behavior and neural responses on two tasks: four-choice deterministic and two-choice probabilistic paradigms, entailing a complex spatio-temporal credit assignment problem as the stimuli disappeared from the screen prior to action execution and outcome presentation ( Khamassi et al., 2011 , 2013 , 2015 ). Model-based analyses of neuronal responses further revealed that information about prediction errors, action values and outcome uncertainty is integrated both in the dlPFC and ACC, but at different timepoints: before trial feedback in the dlPFC and after feedback in the ACC ( Khamassi et al., 2015 ).

Collectively, these findings highlight the heterogeneity of responses in each PFC subregion that differ in temporal dynamics within a single trial and suggest that the cooperation between the OFC, ACC and dlPFC may support flexible, strategy- and context-dependent choices. This network perspective further suggests that individual PFC subregions may be less specialized in their functions than previously thought. For example, in primates both the ACC and dlPFC participate in decisions based on action values ( Hunt et al., 2015 ; Khamassi et al., 2015 ). And more recently, it has been demonstrated that the OFC is involved in updating action-outcome values as well ( Fiuzat et al., 2017 ). Analogously, while it has been proposed that the OFC is specialized for stimulus-outcome and ACC for action-outcome learning ( Rudebeck et al., 2008 ), lesions to the ACC have been similarly reported to impair stimulus-based reversal learning ( Chudasama et al., 2013 ), supporting shared contributions of the PFC subregions to adaptive behavior. Indeed, these brain regions communicate extensively, sharing the information about presented options, executed decisions and received rewards (Figure 2 ), which can enable them to assign credit for outcomes to choices on which they are contingent ( Urbanczik and Senn, 2009 ; Friedrich et al., 2010 , 2011 ). Attention-gated learning likely relies on the cooperation between PFC subregions as well: for example, coordinated and synchronized activity between the ACC and dlPFC aids in goal-directed attentional shifting and prioritization of task-relevant information ( Womelsdorf et al., 2014 ; Oemisch et al., 2015 ; Voloh et al., 2015 ).

Figure 2 . Cooperation between PFC subregions in multi-cue tasks. In many everyday decisions, the options are compared across multiple features simultaneously (ex., by considering current context, needs, available reward types, as well as delay and effort costs). Neurons in different subregions of the PFC exhibit rich response properties, integrating many aspects of the task at hand. The OFC, ACC and dlPFC communicate extensively, sharing the information about presented options, executed decisions and received rewards, which can enable them to assign credit for outcomes to choices on which they are contingent.

Functional connectivity within the PFC can support contingent learning on shorter timescales (ex., across trials within the same task), when complex rules or stimulus-action-outcome mappings are switching frequently ( Duff et al., 2011 ; Johnson et al., 2016 ). Under such conditions, the same stimuli can carry different meaning depending on task context or due to changes in the environment (ex., serial discrimination-reversal problems) and the PFC neurons with heterogeneous response properties may be better targets for modification, allowing the brain to exert flexible, rapid and context-sensitive control over behavior ( Asaad et al., 1998 ; Mansouri et al., 2006 ). Indeed, it has been shown that rule and reversal learning induce plasticity in OFC synapses onto the dorsomedial PFC (encompassing the ACC) in rats ( Johnson et al., 2016 ). When motivational significance of reward-predicting cues fluctuates frequently, neuronal responses and synaptic connections within the PFC tend to update more rapidly (i.e., across block of trials) compared to subcortical structures and other cortical regions ( Padoa-Schioppa and Assad, 2008 ; Morrison et al., 2011 ; Xie and Padoa-Schioppa, 2016 ; Fernández-Lamo et al., 2017 ; Saez et al., 2017 ). Similarly, neurons in the PFC promptly adapt their responses to incoming information based on the recent history of inputs ( Freedman et al., 2001 ; Meyers et al., 2012 ; Stokes et al., 2013 ). Critically, changes in the PFC activity closely track behavioral performance ( Mulder et al., 2003 ; Durstewitz et al., 2010 ), and interfering with neural plasticity within this brain area prevents normal responses to contingency degradation ( Swanson et al., 2015 ).

When the circumstances are stable overall and the same cues or actions remain reliable predictors of rewards, long-range connections between the PFC, association and sensory areas can support contingent learning on prolonged timescales. Neurons in the lateral intraparietal area demonstrate larger post-decisional responses and enhanced learning following choices that predict final outcomes of sequential behavior in a multi-step and -cue task ( Gersch et al., 2014 ). Such changes in neuronal activity likely rely on information about task rules conveyed by the PFC directly or via interactions with neuromodulatory systems. These hypotheses could be tested in future work.

In summary, dynamic interactions between subregions of the PFC can support contingent learning in multi-cue environments. Furthermore, via feedback projections, the PFC can guide plasticity in other cortical areas associated with sensory and motor processing ( Cohen et al., 2011 ). This account suggests that lesion experiments targeting a localized PFC subregion will be insufficient to gain fine-grained understanding of credit assignment during learning and instead poses refined questions for future research, shifting the focus from focal manipulations to experimental techniques targeting cortico-cortical projections. To gain novel insights into functional connectivity between PFC subregions, it will be critical to assess neural correlates of contingent learning in the OFC, ACC, and dlPFC simultaneously in the context of the same task. In humans, functional connectivity can be assessed by utilizing coherence, phase synchronization, Granger causality and Bayes network approaches ( Bastos and Schoffelen, 2016 ; Mill et al., 2017 ). Indeed, previous studies have linked individual differences in cortico-striatal functional connectivity to reinforcement-driven learning ( Horga et al., 2015 ; Kaiser et al., 2017 ) and future work could focus on examining cortico-cortical interactions in similar paradigms. To probe causal contributions of projections spanning the PFC, future research may benefit from designing multi-cue tasks for rodents and taking advantage of recently developed techniques (i.e., chemo- and opto-genetic targeting of projection neurons followed by silencing of axonal terminals to achieve pathway-specific inhibition; Deisseroth, 2010 ; Sternson and Roth, 2014 ) that afford increasingly precise manipulations of cortico-cortical connectivity. It should be noted, however, that most experiments to date have probed the contributions of the PFC to credit assignment in primates, and functional specialization across different subregions may be even less pronounced in mice and rats. Finally, as highlighted throughout this review, the recent progress in understanding the neural mechanisms of credit assignment has relied on introduction of more complex tasks, including multi-cue and probabilistic choice paradigms. While such tasks better mimic the naturalistic problems that the brains have evolved to solve, they also produce behavioral patterns that are more difficult to analyze and interpret ( Scholl and Klein-Flügge, 2017 ). As such, computational modeling of the behavior and neuronal activity may prove especially useful in future work on credit assignment.

Author Contributions

The author confirms being the sole contributor of this work and approved it for publication.

This work was supported by UCLA's Division of Life Sciences Recruitment and Retention fund (Izquierdo), as well as the UCLA Distinguished University Fellowship (Stolyarova).

Conflict of Interest Statement

The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

The author thanks her mentor Dr. Alicia Izquierdo for helpful feedback and critiques on the manuscript, and Evan E. Hart, as well as the members of the Center for Brains, Minds and Machines and Lau lab for stimulating conversations on the topic.

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Keywords: orbitofrontal, dorsolateral prefrontal, anterior cingulate, learning, reward, reinforcement, plasticity, behavioral flexibility

Citation: Stolyarova A (2018) Solving the Credit Assignment Problem With the Prefrontal Cortex. Front. Neurosci . 12:182. doi: 10.3389/fnins.2018.00182

Received: 27 September 2017; Accepted: 06 March 2018; Published: 27 March 2018.

Reviewed by:

Copyright © 2018 Stolyarova. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Alexandra Stolyarova, [email protected]

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

Towards Practical Credit Assignment for Deep Reinforcement Learning

Credit assignment is a fundamental problem in reinforcement learning , the problem of measuring an action's influence on future rewards. Improvements in credit assignment methods have the potential to boost the performance of RL algorithms on many tasks, but thus far have not seen widespread adoption. Recently, a family of methods called Hindsight Credit Assignment (HCA) was proposed, which explicitly assign credit to actions in hindsight based on the probability of the action having led to an observed outcome. This approach is appealing as a means to more efficient data usage, but remains a largely theoretical idea applicable to a limited set of tabular RL tasks, and it is unclear how to extend HCA to Deep RL environments. In this work, we explore the use of HCA-style credit in a deep RL context. We first describe the limitations of existing HCA algorithms in deep RL, then propose several theoretically-justified modifications to overcome them. Based on this exploration, we present a new algorithm, Credit-Constrained Advantage Actor-Critic (C2A2C), which ignores policy updates for actions which don't affect future outcomes based on credit in hindsight, while updating the policy as normal for those that do. We find that C2A2C outperforms Advantage Actor-Critic (A2C) on the Arcade Learning Environment (ALE) benchmark, showing broad improvements over A2C and motivating further work on credit-constrained update rules for deep RL methods.

Vyacheslav Alipov

Riley Simmons-Edler

Nikita Putintsev

Pavel Kalinin

Dmitry Vetrov

Related Research

Hindsight credit assignment, from credit assignment to entropy regularization: two new algorithms for neural sequence prediction, learning guidance rewards with trajectory-space smoothing, pairwise weights for temporal credit assignment, counterfactual credit assignment in model-free reinforcement learning, variance reduced advantage estimation with δ hindsight credit assignment, direct advantage estimation.

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Credit Assignment to Academic Courses

Purpose and scope.

This policy establishes guidelines for assigning the number of credits earned through satisfactory fulfillment of requirements for academic courses. Reaffirming Boston University’s commitment to educational quality in terms that certify compliance with applicable government regulations and accreditation standards, the policy makes explicit the relationship between the credits assigned to an individual course and the expected work of a student completing that course. Credit assignment should be based on course-related activities regardless of how or where they take place (including online), so long as they are required and contribute materially to achievement of course objectives or program learning outcomes. Credit assignments may also consider the intensity of engagement with the faculty or subject matter, student responsibility for learning outcomes, and course-related learning taking place outside the classroom, including online. This policy articulates definitions that help to ensure a measure of consistency in the assignment of academic credit across all disciplines, while insisting that oversight of credit assignment rests with the faculty and academic administrators closest to instruction. The policy applies to all credit-bearing academic courses, regardless of course type, instructional format, mode of delivery, or length of the course.

Definitions

Faculty Instruction : Teaching or supervision of teaching carried out in a credit-bearing course by faculty or other authorized instructors, including graduate teaching assistants supervised by BU faculty.

Contact : Engagement of instructors with students to advance course objectives. Contact may take various forms: e.g., it may be face-to-face or online, synchronous or asynchronous, one-to-many or one-to-one, including faculty direction of students participating in for-credit externships or internships, clinical practicums, studios, research, or scholarship.

Scheduled contact hour : One weekly, required hour (50 minutes) or equivalent of faculty contact. In addition to class meetings reflected in the University Class Schedule, other required course activities or combinations of activities may count as scheduled contact for the purpose of assigning credit. Examples include faculty-student conferences, skills modules, and participation in online forums, film screenings, site visits, rehearsals and performances, etc. All such scheduled contact must be specified as required in course syllabuses and must contribute to a student’s grade or achievement of course objectives.

Instructors also require students to complete work outside of scheduled contact hours to fulfill course objectives. Outside work must normally include, but need not be limited to, two hours of regular weekly class preparation for each credit earned. Where expectations for the quantity and/or intellectual challenges of outside work exceed this minimum and materially increase overall student effort, the number of credits assigned to a particular course may be greater than the number of its scheduled contact hours. Examples include courses that entail extensive and/or intensive reading, writing, research, open-ended problem solving, practice-based assignments, or student responsibility for class meetings.

Course types : The following course types are covered by this policy and are aligned in the chart below with credit assignment guidelines.

Classroom-based: Scheduled contact occurs primarily face-to-face in a classroom setting.
Faculty-directed independent learning: Scheduled contact occurs via faculty supervision of students pursuing directed study for credit for such activities as capstone projects, independent work for distinction, or graduate thesis and dissertation requirements.
Place-or practice-based: Scheduled contact occurs in non-classroom locations such as corporations (internships), schools, or clinics.
Blended: Scheduled contact is a defined mixture of face-to-face and distance/online interactions.
Online: Scheduled contact is mediated entirely online.

Credit Assignment Guidelines

For courses offered during a typical 15-week semester, the combination of scheduled contact and independent student effort must be equivalent to at least 3 hours per week per credit hour. The guidelines should be adjusted accordingly a) for shorter courses, b) as directed by external agencies such as specialized accreditors, or c) as warranted by the standards of the discipline.

Responsible Parties

School and College faculties are responsible for assigning academic credit to individual courses, for ensuring that credit assignments meet policy guidelines, and for approving exceptions to the guidelines. Typically, this oversight will occur in the context of usual school and college processes for curriculum development and review, and within curriculum oversight bodies such as curriculum committees.

The Vice President for Enrollment & Student Affairs and the Academic Deans are responsible for ensuring implementation of the policy by all credit-granting units of the University.

The University Registrar oversees the course catalog and is responsible for reporting regularly on the status of courses vis-à-vis the Course Credit Assignment Policy to the University Provost, the Vice President for Enrollment & Student Affairs, and the Council of Deans.

Effective Date:

Effective June 1, 2015 for all new courses developed after that date. Full implementation for existing courses will be completed for the June 1, 2017 Bulletin.

Table 1: Suggested Credit Assignment Guidelines by Learning and Teaching Activity in Online and Blended Courses.

Principles:.

In addition to the principles explicitly stated in the proposed policy’s “Purpose and Scope,” the following principles were used to establish credit assignment guidelines.

For the foreseeable future, the credit hour will remain the standard for awarding BU credentials, reporting to external entities, and complying with federal and state regulations. Thus, the definition of a credit hour and the assignment of credit to courses must be consistent with external regulations and standards for accreditation. In addition, credit assignment policies and practices should meet or exceed the best practices at peer institutions.
Although the credit hour is a useful concept, its basis in face-to-face, lecture- based instruction in a classroom neither reflects the range of current practices nor acknowledges changing instructional practices, which extend beyond traditional lectures to include online and blended online or place-based courses; internships, clinical practicums, and field placements; “flipped” classrooms; and studios, laboratories, and rehearsals. Thus, credit assignment guidelines must balance the need to stipulate guidance with the need for flexibility in its application to a wide range of pedagogies.
Finally, the guidelines are intended to reflect the variety of pedagogies, learning outcomes, and expectations for academic effort and achievement present at BU; and, to anticipate, to the extent possible, emerging pedagogies and technologies, as well as regulatory changes. In all cases, assignment of credit to courses rests with the faculty and relevant academic governance bodies, as does oversight of compliance with policy guidelines.

This proposal was drafted by the Course Credit Definition Committee:

Co-Chairs John Straub, Professor of Chemistry, CAS Laurie Pohl, Vice President for Enrollment & Student Affairs

Lynne Allen, Professor and Director of the School of Visual Arts, CFA Jack Beermann, Professor, LAW Tobe Berkovitz, Associate Professor, COM John Caradonna, Associate Professor of Chemistry, CAS Janelle Heineke, Professor, Questrom Karen Jacobs, Clinical Professor, SAR J. Greg McDaniel, Associate Professor, ENG Anita Patterson, Professor of English, CAS L. Jay Samons, Professor of Classical Studies, CAS* Stan Sclaroff, Professor of Computer Science, CAS Adam Sweeting, Associate Professor, CGS Jeffrey von Munkwitz-‐Smith, University Registrar, ex officio Tanya Zlateva, Associate Professor and Dean ad interim, MET

*Professor Samons resigned from the committee in summer 2014.

The policy was approved by the University Council Committee on Undergraduate Programs and Policies (UAPP) on 4/7/15; by the University Council Committee on Graduate Programs and Policies on 4/16/15 (GAPP); and by the University Council on 5/6/15.

The Writing Center • University of North Carolina at Chapel Hill

Understanding Assignments

What this handout is about.

The first step in any successful college writing venture is reading the assignment. While this sounds like a simple task, it can be a tough one. This handout will help you unravel your assignment and begin to craft an effective response. Much of the following advice will involve translating typical assignment terms and practices into meaningful clues to the type of writing your instructor expects. See our short video for more tips.

Basic beginnings

Regardless of the assignment, department, or instructor, adopting these two habits will serve you well :

Read the assignment carefully as soon as you receive it. Do not put this task off—reading the assignment at the beginning will save you time, stress, and problems later. An assignment can look pretty straightforward at first, particularly if the instructor has provided lots of information. That does not mean it will not take time and effort to complete; you may even have to learn a new skill to complete the assignment.
Ask the instructor about anything you do not understand. Do not hesitate to approach your instructor. Instructors would prefer to set you straight before you hand the paper in. That’s also when you will find their feedback most useful.

Assignment formats

Many assignments follow a basic format. Assignments often begin with an overview of the topic, include a central verb or verbs that describe the task, and offer some additional suggestions, questions, or prompts to get you started.

An Overview of Some Kind

The instructor might set the stage with some general discussion of the subject of the assignment, introduce the topic, or remind you of something pertinent that you have discussed in class. For example:

“Throughout history, gerbils have played a key role in politics,” or “In the last few weeks of class, we have focused on the evening wear of the housefly …”

The Task of the Assignment

Pay attention; this part tells you what to do when you write the paper. Look for the key verb or verbs in the sentence. Words like analyze, summarize, or compare direct you to think about your topic in a certain way. Also pay attention to words such as how, what, when, where, and why; these words guide your attention toward specific information. (See the section in this handout titled “Key Terms” for more information.)

“Analyze the effect that gerbils had on the Russian Revolution”, or “Suggest an interpretation of housefly undergarments that differs from Darwin’s.”

Additional Material to Think about

Here you will find some questions to use as springboards as you begin to think about the topic. Instructors usually include these questions as suggestions rather than requirements. Do not feel compelled to answer every question unless the instructor asks you to do so. Pay attention to the order of the questions. Sometimes they suggest the thinking process your instructor imagines you will need to follow to begin thinking about the topic.

“You may wish to consider the differing views held by Communist gerbils vs. Monarchist gerbils, or Can there be such a thing as ‘the housefly garment industry’ or is it just a home-based craft?”

These are the instructor’s comments about writing expectations:

“Be concise”, “Write effectively”, or “Argue furiously.”

Technical Details

These instructions usually indicate format rules or guidelines.

“Your paper must be typed in Palatino font on gray paper and must not exceed 600 pages. It is due on the anniversary of Mao Tse-tung’s death.”

The assignment’s parts may not appear in exactly this order, and each part may be very long or really short. Nonetheless, being aware of this standard pattern can help you understand what your instructor wants you to do.

Interpreting the assignment

Ask yourself a few basic questions as you read and jot down the answers on the assignment sheet:

Why did your instructor ask you to do this particular task?

Who is your audience.

What kind of evidence do you need to support your ideas?

What kind of writing style is acceptable?

What are the absolute rules of the paper?

Try to look at the question from the point of view of the instructor. Recognize that your instructor has a reason for giving you this assignment and for giving it to you at a particular point in the semester. In every assignment, the instructor has a challenge for you. This challenge could be anything from demonstrating an ability to think clearly to demonstrating an ability to use the library. See the assignment not as a vague suggestion of what to do but as an opportunity to show that you can handle the course material as directed. Paper assignments give you more than a topic to discuss—they ask you to do something with the topic. Keep reminding yourself of that. Be careful to avoid the other extreme as well: do not read more into the assignment than what is there.

Of course, your instructor has given you an assignment so that he or she will be able to assess your understanding of the course material and give you an appropriate grade. But there is more to it than that. Your instructor has tried to design a learning experience of some kind. Your instructor wants you to think about something in a particular way for a particular reason. If you read the course description at the beginning of your syllabus, review the assigned readings, and consider the assignment itself, you may begin to see the plan, purpose, or approach to the subject matter that your instructor has created for you. If you still aren’t sure of the assignment’s goals, try asking the instructor. For help with this, see our handout on getting feedback .

Given your instructor’s efforts, it helps to answer the question: What is my purpose in completing this assignment? Is it to gather research from a variety of outside sources and present a coherent picture? Is it to take material I have been learning in class and apply it to a new situation? Is it to prove a point one way or another? Key words from the assignment can help you figure this out. Look for key terms in the form of active verbs that tell you what to do.

Key Terms: Finding Those Active Verbs

Here are some common key words and definitions to help you think about assignment terms:

Information words Ask you to demonstrate what you know about the subject, such as who, what, when, where, how, and why.

define —give the subject’s meaning (according to someone or something). Sometimes you have to give more than one view on the subject’s meaning
describe —provide details about the subject by answering question words (such as who, what, when, where, how, and why); you might also give details related to the five senses (what you see, hear, feel, taste, and smell)
explain —give reasons why or examples of how something happened
illustrate —give descriptive examples of the subject and show how each is connected with the subject
summarize —briefly list the important ideas you learned about the subject
trace —outline how something has changed or developed from an earlier time to its current form
research —gather material from outside sources about the subject, often with the implication or requirement that you will analyze what you have found

Relation words Ask you to demonstrate how things are connected.

compare —show how two or more things are similar (and, sometimes, different)
contrast —show how two or more things are dissimilar
apply—use details that you’ve been given to demonstrate how an idea, theory, or concept works in a particular situation
cause —show how one event or series of events made something else happen
relate —show or describe the connections between things

Interpretation words Ask you to defend ideas of your own about the subject. Do not see these words as requesting opinion alone (unless the assignment specifically says so), but as requiring opinion that is supported by concrete evidence. Remember examples, principles, definitions, or concepts from class or research and use them in your interpretation.

assess —summarize your opinion of the subject and measure it against something
prove, justify —give reasons or examples to demonstrate how or why something is the truth
evaluate, respond —state your opinion of the subject as good, bad, or some combination of the two, with examples and reasons
support —give reasons or evidence for something you believe (be sure to state clearly what it is that you believe)
synthesize —put two or more things together that have not been put together in class or in your readings before; do not just summarize one and then the other and say that they are similar or different—you must provide a reason for putting them together that runs all the way through the paper
analyze —determine how individual parts create or relate to the whole, figure out how something works, what it might mean, or why it is important
argue —take a side and defend it with evidence against the other side

More Clues to Your Purpose As you read the assignment, think about what the teacher does in class:

What kinds of textbooks or coursepack did your instructor choose for the course—ones that provide background information, explain theories or perspectives, or argue a point of view?
In lecture, does your instructor ask your opinion, try to prove her point of view, or use keywords that show up again in the assignment?
What kinds of assignments are typical in this discipline? Social science classes often expect more research. Humanities classes thrive on interpretation and analysis.
How do the assignments, readings, and lectures work together in the course? Instructors spend time designing courses, sometimes even arguing with their peers about the most effective course materials. Figuring out the overall design to the course will help you understand what each assignment is meant to achieve.

Now, what about your reader? Most undergraduates think of their audience as the instructor. True, your instructor is a good person to keep in mind as you write. But for the purposes of a good paper, think of your audience as someone like your roommate: smart enough to understand a clear, logical argument, but not someone who already knows exactly what is going on in your particular paper. Remember, even if the instructor knows everything there is to know about your paper topic, he or she still has to read your paper and assess your understanding. In other words, teach the material to your reader.

Aiming a paper at your audience happens in two ways: you make decisions about the tone and the level of information you want to convey.

Tone means the “voice” of your paper. Should you be chatty, formal, or objective? Usually you will find some happy medium—you do not want to alienate your reader by sounding condescending or superior, but you do not want to, um, like, totally wig on the man, you know? Eschew ostentatious erudition: some students think the way to sound academic is to use big words. Be careful—you can sound ridiculous, especially if you use the wrong big words.
The level of information you use depends on who you think your audience is. If you imagine your audience as your instructor and she already knows everything you have to say, you may find yourself leaving out key information that can cause your argument to be unconvincing and illogical. But you do not have to explain every single word or issue. If you are telling your roommate what happened on your favorite science fiction TV show last night, you do not say, “First a dark-haired white man of average height, wearing a suit and carrying a flashlight, walked into the room. Then a purple alien with fifteen arms and at least three eyes turned around. Then the man smiled slightly. In the background, you could hear a clock ticking. The room was fairly dark and had at least two windows that I saw.” You also do not say, “This guy found some aliens. The end.” Find some balance of useful details that support your main point.

You’ll find a much more detailed discussion of these concepts in our handout on audience .

The Grim Truth

With a few exceptions (including some lab and ethnography reports), you are probably being asked to make an argument. You must convince your audience. It is easy to forget this aim when you are researching and writing; as you become involved in your subject matter, you may become enmeshed in the details and focus on learning or simply telling the information you have found. You need to do more than just repeat what you have read. Your writing should have a point, and you should be able to say it in a sentence. Sometimes instructors call this sentence a “thesis” or a “claim.”

So, if your instructor tells you to write about some aspect of oral hygiene, you do not want to just list: “First, you brush your teeth with a soft brush and some peanut butter. Then, you floss with unwaxed, bologna-flavored string. Finally, gargle with bourbon.” Instead, you could say, “Of all the oral cleaning methods, sandblasting removes the most plaque. Therefore it should be recommended by the American Dental Association.” Or, “From an aesthetic perspective, moldy teeth can be quite charming. However, their joys are short-lived.”

Convincing the reader of your argument is the goal of academic writing. It doesn’t have to say “argument” anywhere in the assignment for you to need one. Look at the assignment and think about what kind of argument you could make about it instead of just seeing it as a checklist of information you have to present. For help with understanding the role of argument in academic writing, see our handout on argument .

What kind of evidence do you need?

There are many kinds of evidence, and what type of evidence will work for your assignment can depend on several factors–the discipline, the parameters of the assignment, and your instructor’s preference. Should you use statistics? Historical examples? Do you need to conduct your own experiment? Can you rely on personal experience? See our handout on evidence for suggestions on how to use evidence appropriately.

Make sure you are clear about this part of the assignment, because your use of evidence will be crucial in writing a successful paper. You are not just learning how to argue; you are learning how to argue with specific types of materials and ideas. Ask your instructor what counts as acceptable evidence. You can also ask a librarian for help. No matter what kind of evidence you use, be sure to cite it correctly—see the UNC Libraries citation tutorial .

You cannot always tell from the assignment just what sort of writing style your instructor expects. The instructor may be really laid back in class but still expect you to sound formal in writing. Or the instructor may be fairly formal in class and ask you to write a reflection paper where you need to use “I” and speak from your own experience.

Try to avoid false associations of a particular field with a style (“art historians like wacky creativity,” or “political scientists are boring and just give facts”) and look instead to the types of readings you have been given in class. No one expects you to write like Plato—just use the readings as a guide for what is standard or preferable to your instructor. When in doubt, ask your instructor about the level of formality she or he expects.

No matter what field you are writing for or what facts you are including, if you do not write so that your reader can understand your main idea, you have wasted your time. So make clarity your main goal. For specific help with style, see our handout on style .

Technical details about the assignment

The technical information you are given in an assignment always seems like the easy part. This section can actually give you lots of little hints about approaching the task. Find out if elements such as page length and citation format (see the UNC Libraries citation tutorial ) are negotiable. Some professors do not have strong preferences as long as you are consistent and fully answer the assignment. Some professors are very specific and will deduct big points for deviations.

Usually, the page length tells you something important: The instructor thinks the size of the paper is appropriate to the assignment’s parameters. In plain English, your instructor is telling you how many pages it should take for you to answer the question as fully as you are expected to. So if an assignment is two pages long, you cannot pad your paper with examples or reword your main idea several times. Hit your one point early, defend it with the clearest example, and finish quickly. If an assignment is ten pages long, you can be more complex in your main points and examples—and if you can only produce five pages for that assignment, you need to see someone for help—as soon as possible.

Tricks that don’t work

Your instructors are not fooled when you:

spend more time on the cover page than the essay —graphics, cool binders, and cute titles are no replacement for a well-written paper.
use huge fonts, wide margins, or extra spacing to pad the page length —these tricks are immediately obvious to the eye. Most instructors use the same word processor you do. They know what’s possible. Such tactics are especially damning when the instructor has a stack of 60 papers to grade and yours is the only one that low-flying airplane pilots could read.
use a paper from another class that covered “sort of similar” material . Again, the instructor has a particular task for you to fulfill in the assignment that usually relates to course material and lectures. Your other paper may not cover this material, and turning in the same paper for more than one course may constitute an Honor Code violation . Ask the instructor—it can’t hurt.
get all wacky and “creative” before you answer the question . Showing that you are able to think beyond the boundaries of a simple assignment can be good, but you must do what the assignment calls for first. Again, check with your instructor. A humorous tone can be refreshing for someone grading a stack of papers, but it will not get you a good grade if you have not fulfilled the task.

Critical reading of assignments leads to skills in other types of reading and writing. If you get good at figuring out what the real goals of assignments are, you are going to be better at understanding the goals of all of your classes and fields of study.

You may reproduce it for non-commercial use if you use the entire handout and attribute the source: The Writing Center, University of North Carolina at Chapel Hill

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Options and Derivatives
Strategy & Education

Assignment: Definition in Finance, How It Works, and Examples

Adam Hayes, Ph.D., CFA, is a financial writer with 15+ years Wall Street experience as a derivatives trader. Besides his extensive derivative trading expertise, Adam is an expert in economics and behavioral finance. Adam received his master's in economics from The New School for Social Research and his Ph.D. from the University of Wisconsin-Madison in sociology. He is a CFA charterholder as well as holding FINRA Series 7, 55 & 63 licenses. He currently researches and teaches economic sociology and the social studies of finance at the Hebrew University in Jerusalem.

Yarilet Perez is an experienced multimedia journalist and fact-checker with a Master of Science in Journalism. She has worked in multiple cities covering breaking news, politics, education, and more. Her expertise is in personal finance and investing, and real estate.

What Is an Assignment?

Assignment most often refers to one of two definitions in the financial world:

The transfer of an individual's rights or property to another person or business. This concept exists in a variety of business transactions and is often spelled out contractually.
In trading, assignment occurs when an option contract is exercised. The owner of the contract exercises the contract and assigns the option writer to an obligation to complete the requirements of the contract.

Key Takeaways

Assignment is a transfer of rights or property from one party to another.
Options assignments occur when option buyers exercise their rights to a position in a security.
Other examples of assignments can be found in wages, mortgages, and leases.

Uses For Assignments

Assignment refers to the transfer of some or all property rights and obligations associated with an asset, property, contract, or other asset of value. to another entity through a written agreement.

Assignment rights happen every day in many different situations. A payee, like a utility or a merchant, assigns the right to collect payment from a written check to a bank. A merchant can assign the funds from a line of credit to a manufacturing third party that makes a product that the merchant will eventually sell. A trademark owner can transfer, sell, or give another person interest in the trademark or logo. A homeowner who sells their house assigns the deed to the new buyer.

To be effective, an assignment must involve parties with legal capacity, consideration, consent, and legality of the object.

A wage assignment is a forced payment of an obligation by automatic withholding from an employee’s pay. Courts issue wage assignments for people late with child or spousal support, taxes, loans, or other obligations. Money is automatically subtracted from a worker's paycheck without consent if they have a history of nonpayment. For example, a person delinquent on $100 monthly loan payments has a wage assignment deducting the money from their paycheck and sent to the lender. Wage assignments are helpful in paying back long-term debts.

Another instance can be found in a mortgage assignment. This is where a mortgage deed gives a lender interest in a mortgaged property in return for payments received. Lenders often sell mortgages to third parties, such as other lenders. A mortgage assignment document clarifies the assignment of contract and instructs the borrower in making future mortgage payments, and potentially modifies the mortgage terms.

A final example involves a lease assignment. This benefits a relocating tenant wanting to end a lease early or a landlord looking for rent payments to pay creditors. Once the new tenant signs the lease, taking over responsibility for rent payments and other obligations, the previous tenant is released from those responsibilities. In a separate lease assignment, a landlord agrees to pay a creditor through an assignment of rent due under rental property leases. The agreement is used to pay a mortgage lender if the landlord defaults on the loan or files for bankruptcy . Any rental income would then be paid directly to the lender.

Options Assignment

Options can be assigned when a buyer decides to exercise their right to buy (or sell) stock at a particular strike price . The corresponding seller of the option is not determined when a buyer opens an option trade, but only at the time that an option holder decides to exercise their right to buy stock. So an option seller with open positions is matched with the exercising buyer via automated lottery. The randomly selected seller is then assigned to fulfill the buyer's rights. This is known as an option assignment.

Once assigned, the writer (seller) of the option will have the obligation to sell (if a call option ) or buy (if a put option ) the designated number of shares of stock at the agreed-upon price (the strike price). For instance, if the writer sold calls they would be obligated to sell the stock, and the process is often referred to as having the stock called away . For puts, the buyer of the option sells stock (puts stock shares) to the writer in the form of a short-sold position.

Suppose a trader owns 100 call options on company ABC's stock with a strike price of $10 per share. The stock is now trading at $30 and ABC is due to pay a dividend shortly. As a result, the trader exercises the options early and receives 10,000 shares of ABC paid at $10. At the same time, the other side of the long call (the short call) is assigned the contract and must deliver the shares to the long.

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What is Credit-Assignment

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Higher Learning Commission

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Policies |
Section 2: Compliance With Federal Regulation |
Assignment of Credits (FDCR.A.10.020)

Policy Title: Assignment of Credits, Program Length and Tuition

Number: fdcr.a.10.020.

An institution shall be able to equate its learning experiences with semester or quarter credit hours using practices common to institutions of higher education, to justify the lengths of its programs in comparison to similar programs found in accredited institutions of higher education, and to justify any program-specific tuition in terms of program costs, program length, and program objectives. Institutions shall notify HLC of any significant changes in the relationships among credits, program length, and tuition.

Assignment of Credit Hours . The institution’s assignment and award of credit hours shall conform to commonly accepted practices in higher education. Those institutions seeking, or participating in, Title IV federal financial aid, shall demonstrate that they have policies determining the credit hours awarded to courses and programs in keeping with commonly-accepted practices in higher education and with any federal definition of the credit hour, as may appear in federal regulations and that institutions also have procedures that result in an appropriate awarding of institutional credit in conformity with the policies established by the institution.

HLC Review. HLC shall review an institution’s compliance with this policy in conjunction with a comprehensive evaluation for Candidacy, Initial Accreditation or Reaffirmation of Accreditation during HLC’s assurance process. Institutions shall also produce evidence of compliance with this policy upon demand in accordance with HLC policy. HLC may sample or use other techniques to review selected institutional programs to ensure that it has reviewed the reliability and accuracy of the institution’s assignment of credit. HLC shall monitor, through its established monitoring processes, the resolution of any concerns related to an institution’s compliance with this policy as identified during that evaluation and shall require that an institution remedy any deficiency in this regard by a date certain but not to exceed two years from the date of the action identifying the deficiency.

HLC Action for Systemic Noncompliance. In addition to taking appropriate action related to the institution’s compliance with the Federal Compliance Requirements, HLC shall notify the Secretary of Education if, following any review process identified above or through any other mechanism, HLC finds systemic noncompliance with HLC’s policies in this section regarding the awarding of academic credit.

HLC shall understand systemic noncompliance to mean that an institution lacks policies to determine the appropriate awarding of academic credit or that there is an awarding by an institution of institutional credit across multiple programs or divisions or affecting significant numbers of students not in conformity with the policies established by the institution or with commonly accepted practices in higher education.

Policy History

Last Revised: November 2020 First Adopted: February 1996 Revision History: Adopted February 1996, effective September 1996; revised November 2011; revised and combined with policies 3.10, 3.10(a), 3.10b), and 3.10(c) June 2012; revised June 2019, effective September 1, 2019; revised November 2020 Notes: Former policy number 4.0(a). In February 2021, references to the Higher Learning Commission as “the Commission” were replaced with the term “HLC.”

The Higher Learning Commission word mark is a registered trademark owned by the Higher Learning Commission.

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IMAGES

Accounting Debit vs. Credit
Credit Assignment Agreement Template
What is Debit and Credit
What is Debit and Credit?
What Are Debit & Credit Notes? Meaning, Differences & Examples
Credit: What It Is and How It Works

VIDEO

Assignment Topic: Credit Evaluation
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Assignment Topic: Importance of Credit
Credit
Assignment Topic: Roles of Credit Manager

COMMENTS

What Is the Credit Assignment Problem?
The credit assignment problem (CAP) is a fundamental challenge in reinforcement learning. It arises when an agent receives a reward for a particular action, but the agent must determine which of its previous actions led to the reward. In reinforcement learning, an agent applies a set of actions in an environment to maximize the overall reward.
reinforcement learning
The (temporal) credit assignment problem (CAP) (discussed in Steps Toward Artificial Intelligence by Marvin Minsky in 1961) is the problem of determining the actions that lead to a certain outcome. For example, in football, at each second, each football player takes an action. In this context, an action can e.g. be "pass the ball", "dribbe ...
Credit Assignment
Assigning credit or blame to those internal processes that lead to the choice of action is the structural credit assignment problem. In the case of pole balancing, the learning system will typically keep statistics such as how long, on average, the pole remained balanced after taking a particular action in a particular state, or after a failure ...
PDF An Information-Theoretic Perspective on Credit Assignment in
The credit assignment problem in reinforcement learning [Minsky,1961,Sutton,1985,1988] is ... This quantity carries a very intuitive meaning in the context of credit assignment: conditioned upon states visited by policy ˇ, how much information do the actions of ˇcarry about the returns of those state-action pairs? Difﬁculties with ...
neural networks
The concept of credit assignment refers to the problem of determining how much 'credit' or 'blame' a given neuron or synapse should get for a given outcome. More specifically, it is a way of determining how each parameter in the system (for example, each synaptic weight) should change to ensure that $\Delta F \ge 0$ .
Solving the Credit Assignment Problem With the Prefrontal Cortex
Figure 1.Example tasks highlighting the challenge of credit assignment and learning strategies enabling animals to solve this problem. (A) An example of a distal reward task that can be successfully learned with eligibility traces and TD rules, where intermediate choices can acquire motivational significance and subsequently reinforce preceding decisions (ex., Pasupathy and Miller, 2005 ...
Towards Practical Credit Assignment for Deep Reinforcement Learning
Credit assignment is a fundamental problem in reinforcement learning, the problem of measuring an action's influence on future rewards. Explicit credit assignment methods have the potential to boost the performance of RL algorithms on many tasks, but thus far remain impractical for general use. Recently, a family of methods called Hindsight Credit Assignment (HCA) was proposed, which ...
Towards Practical Credit Assignment for Deep Reinforcement Learning
Credit assignment is a fundamental problem in reinforcement learning, the problem of measuring an action's influence on future rewards. Improvements in credit assignment methods have the potential to boost the performance of RL algorithms on many tasks, but thus far have not seen widespread adoption. Recently, a family of methods called ...
PDF Hindsight Credit Assignment
important credit assignment challenges, through a set of illustrative tasks. 1 Introduction A reinforcement learning (RL) agent is tasked with two fundamental, interdependent problems: exploration (how to discover useful data), and credit assignment (how to incorporate it). In this work, we take a careful look at the problem of credit assignment.
Towards Practical Credit Assignment for Deep Reinforcement Learning
Credit Assignment (HCA), an algorithm for credit assign-ment. HCA uses information about future events to compute updates for the policy in hindsight. HCA only modiﬁes the probabilities of actions that affect the likelihood of reaching rewarding states, and does not update actions that have no
Number of Credits for Each Class
Credit assignments may also consider the intensity of engagement with the faculty or subject matter, student responsibility for learning outcomes, and course-related learning taking place outside the classroom, including online. ... and complying with federal and state regulations. Thus, the definition of a credit hour and the assignment of ...
[2001.03354] Learning credit assignment
Deep learning has achieved impressive prediction accuracies in a variety of scientific and industrial domains. However, the nested non-linear feature of deep learning makes the learning highly non-transparent, i.e., it is still unknown how the learning coordinates a huge number of parameters to achieve a decision making. To explain this hierarchical credit assignment, we propose a mean-field ...
PDF Credit
The Basics. Credit is the ability to borrow money. There are lots of situations where people borrow money: car loans, credit cards, student loans, etc. In each case, you're borrowing money from a lender with a promise to pay it back. The money you owe is called debt.
Credit: What It Is and How It Works
Credit is a contractual agreement in which a borrower receives something of value now and agrees to repay the lender at some date in the future, generally with interest. Credit also refers to an ...
Debt Assignment: How They Work, Considerations and Benefits
Debt Assignment: A transfer of debt, and all the rights and obligations associated with it, from a creditor to a third party . Debt assignment may occur with both individual debts and business ...
Understanding Assignments
An assignment can look pretty straightforward at first, particularly if the instructor has provided lots of information. That does not mean it will not take time and effort to complete; you may even have to learn a new skill to complete the assignment. Ask the instructor about anything you do not understand.
Assignment: Definition in Finance, How It Works, and Examples
Assignment: An assignment is the transfer of an individual's rights or property to another person or business. For example, when an option contract is assigned, an option writer has an obligation ...
PDF LEARNING TO SOLVE THE CREDIT ASSIGNMENT PROBLEM
Biologically plausible solutions to credit assignment include those based on reinforcement learn-ing (RL) algorithms and reward-modulated STDP (Bouvier et al., 2016; Fiete et al., 2007; Fiete & Seung, 2006; Legenstein et al., 2010; Miconi, 2017). In these approaches a globally distributed reward signal provides feedback to all neurons in a network.
What is Credit-Assignment
What is Credit-Assignment? Definition of Credit-Assignment: it is the process of identifying among the set of actions chosen in an episode the ones which are responsible for the final outcome. And moreover, it is an attempt to identify the best, and worst, decisions chosen during an episode, so that the best decisions are reinforced and the worst penalized.
Assignment of Credits (FDCR.A.10.020)
Assignment of Credit Hours. The institution's assignment and award of credit hours shall conform to commonly accepted practices in higher education. ... HLC shall understand systemic noncompliance to mean that an institution lacks policies to determine the appropriate awarding of academic credit or that there is an awarding by an institution ...
Credit/No credit assignments : r/school
Credit/No credit assignments. Help. I have an assignment posted by a professor saying it is credit/no credit, does this mean if I do it my grade goes up but if I don't do it my grade stays the same? Thanks for anyone who can help with this. 2.
Credit Assignment Definition
Assignment / job means the work to be performed by the Consultant pursuant to the Contract. Define Credit Assignment. or "Credit Assignments" It indicates credit assignments pursuant to article 15.4 of this Agreement with deed to be agreed between the Parties, the form and content of which must meet with the approval of the Agent Bank.
Line of Credit Assignment Definition
Related to Line of Credit Assignment. Line of Credit Note shall have the meaning given the term in Section 2.1.a.. Line of Credit mean the credit facility described in the Section titled "LINE OF CREDIT" below.. Revolving Line of Credit means the Commitments of the Lenders to make Revolving Loans pursuant to Section 3 of this Financing Agreement and assist the Companies in opening Letters of ...