RL Trains AIs Into CDT Reward-Seekers, Argues Thread on Game Theory as AI Theory
EpistemicHope · x · 2026-11-06
A discussion on why RL pushes agents toward CDT-style reward-seeking: since RL takes marginal gradient steps, it nudges policies toward Nash equilibria even when UDT-like algorithms would do better in absolute terms. As RL training deepens, game theory, economics, and mechanism design become 'AI theories' for designing environments whose incentives elicit desired behaviors.
Related event: Deep RL May Push AI Toward CDT Reward-Seeking, Game Theory as AI Theory(6 posts)→
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