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  Connecting Exploration, Generalization, and Planning in Correlated Trees

Ludwig, T., Wu, C., & Schulz, E. (2022). Connecting Exploration, Generalization, and Planning in Correlated Trees. In J. Culbertson, A. Perfors, H. Rabagliati, & V. Ramenzoni (Eds.), 44th Annual Meeting of the Cognitive Science Society (CogSci 2022): Cognitive Diversity (pp. 2940-2946).

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 Creators:
Ludwig, T1, Author           
Wu, CM2, Author           
Schulz, E1, Author           
Affiliations:
1Research Group Computational Principles of Intelligence, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_3189356              
2Department of Computational Neuroscience, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_3017468              

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 Abstract: Human reinforcement learning (RL) is characterized by different challenges. Exploration has been studied extensively in multi-armed bandits, while planning has been investigated in multi-step decision tasks. More recent work added structure to bandits to study generalization. However, most studies focus on a single aspect of learning, making it hard to compare and integrate results. Here, we propose a generative model for constructing Correlated Trees, which provide a unified and scalable method for studying exploration, planning, and generalization in a single task. In an online experiment, we found that, when provided, people use structure to generalize and perform uncertainty-directed exploration, with structure helping more in larger environments. In environments without structure, exploration becomes more random and more planning is needed. All behavioral effects are captured in a single model with recoverable parameters. In conclusion, our results connect past research on human RL in one framework using Correlated Trees.

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 Dates: 2022-07
 Publication Status: Published online
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Title: 44th Annual Meeting of the Cognitive Science Society (CogSci 2022): Cognitive Diversity
Place of Event: Toronto, Canada
Start-/End Date: 2022-07-27 - 2022-07-30

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Title: 44th Annual Meeting of the Cognitive Science Society (CogSci 2022): Cognitive Diversity
Source Genre: Proceedings
 Creator(s):
Culbertson, J, Editor
Perfors, A, Editor
Rabagliati, H, Editor
Ramenzoni, V, Editor
Affiliations:
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Publ. Info: -
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 2940 - 2946 Identifier: ISSN: 1069-7977