Selective imitation on the basis of reward function similarity
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Abstract (arXiv)
Imitation is a key component of human social behavior, and is widely used by both children and adults as a way to navigate uncertain or unfamiliar situations. But in an environment populated by multiple heterogeneous agents pursuing different goals or objectives, indiscriminate imitation is unlikely to be an effective strategy -- the imitator must instead determine who is most useful to copy. There are likely many factors that play into these judgements, depending on context and availability of information. Here we investigate the hypothesis that these decisions involve inferences about other agents' reward functions. We suggest that people preferentially imitate the behavior of others they deem to have similar reward functions to their own. We further argue that these inferences can be made on the basis of very sparse or indirect data, by leveraging an inductive bias toward positing the existence of different textitgroups or textittypes of people with similar reward functions, allowing learners to select imitation targets without direct evidence of alignment.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 3 of its 28 references that are in the map. First posted on arXiv 12 May 2023.
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3 of 28 references.
References · 3
- 2018An Algorithmic Perspective on Imitation Learningcited by 459
- 2020Online Bayesian Goal Inference for Boundedly-Rational Planning Agentscited by 68
- 2022GriddlyJS: A Web IDE for Reinforcement Learningcited by 4
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