Comparing Reinforcement Learning and Human Learning With the Game of Hidden Rules

Comparing Reinforcement Learning and Human Learning With the Game of Hidden Rules

Human-machine systems, especially those involving reinforcement learning (RL), are becoming increasingly common across application domains. Designing these systems to be effective and reliable requires a task-oriented understanding of both human learning (HL) and RL. In particular, how does the stru...

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Bibliographic Details
Main Authors: Eric M. Pulick, Vladimir Menkov, Yonatan D. Mintz, Paul B. Kantor, Vicki M. Bier
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Artificial intelligence
benchmark testing
cognition
human intelligence
man-machine systems
problem solving
Online Access:https://ieeexplore.ieee.org/document/10510453/

Internet

https://ieeexplore.ieee.org/document/10510453/

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