Literature DB >> 28341268

Social is special: A normative framework for teaching with and learning from evaluative feedback.

Mark K Ho1, James MacGlashan2, Michael L Littman3, Fiery Cushman4.   

Abstract

Humans often attempt to influence one another's behavior using rewards and punishments. How does this work? Psychologists have often assumed that "evaluative feedback" influences behavior via standard learning mechanisms that learn from environmental contingencies. On this view, teaching with evaluative feedback involves leveraging learning systems designed to maximize an organism's positive outcomes. Yet, despite its parsimony, programs of research predicated on this assumption, such as ones in developmental psychology, animal behavior, and human-robot interaction, have had limited success. We offer an explanation by analyzing the logic of evaluative feedback and show that specialized learning mechanisms are uniquely favored in the case of evaluative feedback from a social partner. Specifically, evaluative feedback works best when it is treated as communicating information about the value of an action rather than as a form of reward to be maximized. This account suggests that human learning from evaluative feedback depends on inferences about communicative intent, goals and other mental states-much like learning from other sources, such as demonstration, observation and instruction. Because these abilities are especially developed in humans, the present account also explains why evaluative feedback is far more widespread in humans than non-human animals.
Copyright © 2017 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Evaluative feedback; Punishment; Reward; Social learning; Teaching; Theory of mind

Mesh:

Year:  2017        PMID: 28341268     DOI: 10.1016/j.cognition.2017.03.006

Source DB:  PubMed          Journal:  Cognition        ISSN: 0010-0277


  11 in total

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7.  Emotion prediction errors guide socially adaptive behaviour.

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8.  Trusting and learning from others: immediate and long-term effects of learning from observation and advice.

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Review 9.  Reinforcement Learning With Human Advice: A Survey.

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Review 10.  Knowing Ourselves Together: The Cultural Origins of Metacognition.

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Journal:  Trends Cogn Sci       Date:  2020-03-24       Impact factor: 20.229

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