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arXiv · 2608.21372

AI Learning and Conceptual Transfer in the Game of Hidden Rules

Christo Mathew·Wentian Wang·Jacob Feldman·Lazaros K. Gallos·Paul B. Kantor·Vladimir Menkov·Hao Wang
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Abstract

This report summarizes the work conducted on the Game of Hidden Rules (GOHR), focusing on reinforcement learning agents trained to infer hidden rules from trial-and-error feedback, representation design, rule difficulty analysis, transfer learning, generalization, and pseudo-bot-assisted human learning analysis. The report focuses on the Transformer-based A2C framework, Feature-Centric and Object-Centric representations, experimental findings, and classification of human learning data.

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Christo Mathew, Wentian Wang, Jacob Feldman, Lazaros K. Gallos, Paul B. Kantor, Vladimir Menkov, Hao Wang. 2026-06-26. AI Learning and Conceptual Transfer in the Game of Hidden Rules. https://arxiv.org/abs/2608.21372

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