Richard Bellman formalizes the mathematical framework for modeling optimization problems where outcomes are partly random and partly under control. His equations govern modern reinforcement learning policies.
Part of the 26 Structural Foundations: How We Teach Machines to Understand Purpose and Human Intent archive. HistoricallyVerified
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