AINeutralarXiv – CS AI · 10h ago6/10
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Illuminating the Three Dogmas of Reinforcement Learning under Evolutionary Light
Researchers challenge three foundational assumptions in reinforcement learning—treating environments as Markov processes, learning as policy optimization, and agents as scalar reward maximizers—proposing instead a framework grounded in evolutionary dynamics and thermodynamic theories of agency. The work suggests reconceptualizing agent learning as adaptation rather than optimization, with goals extending beyond simple reward signals.