Social Concepts Simplify Complex Reinforcement Learning

被引:2
|
作者
Hackel, Leor M. [1 ]
Kalkstein, David A. [2 ]
机构
[1] Univ Southern Calif, Dept Psychol, Los Angeles, CA 90007 USA
[2] Stanford Univ, Dept Psychol, Stanford, CA USA
关键词
concepts; generalization; reinforcement learning; relational reasoning; rewards; social cognition; open data; open materials; preregistered; RELATIONAL LANGUAGE; INFERENCES; KNOWLEDGE; SELECTION; CHOICES;
D O I
10.1177/09567976231180587
中图分类号
B84 [心理学];
学科分类号
04 ; 0402 ;
摘要
Humans often generalize rewarding experiences across abstract social roles. Theories of reward learning suggest that people generalize through model-based learning, but such learning is cognitively costly. Why do people seem to generalize across social roles with ease? Humans are social experts who easily recognize social roles that reflect familiar semantic concepts (e.g., "helper" or "teacher"). People may associate these roles with model-free reward (e.g., learning that helpers are rewarding), allowing them to generalize easily (e.g., interacting with novel individuals identified as helpers). In four online experiments with U.S. adults (N = 577), we found evidence that social concepts ease complex learning (people generalize more and at faster speed) and that people attach reward directly to abstract roles (they generalize even when roles are unrelated to task structure). These results demonstrate how familiar concepts allow complex behavior to emerge from simple strategies, highlighting social interaction as a prototype for studying cognitive ease in the face of environmental complexity.
引用
收藏
页码:968 / 983
页数:16
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