AINeutralarXiv – CS AI · 6h ago6/10
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Compositional Behavioral Semantics for State Abstraction in Reinforcement Learning
Researchers present a unified mathematical framework for understanding how behavioral structures in reinforcement learning systems are preserved when models are simplified through state abstraction. The work establishes compositional principles for transferring behavioral guarantees between abstract and concrete systems, providing theoretical foundations for scaling RL to complex structured environments.