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Kudos AI

Tagged “policy-iteration”

2 articles.

5 min readReinforcement Learning

The Parameter Nobody Chooses

The living reward in a grid world is written down once and never discussed, and the optimal policy is a step function of it: eight thresholds between -3 and 0, each flipping exactly one square. The textbook value of -0.04 sits 0.0048 away from the one that decides whether the agent takes the shortcut past the pit, and above -0.0221, when steps are nearly free, the optimal move in one corner is to walk into a wall on purpose.

Artificial Intelligence
9 min readReinforcement Learning

Markov Decision Processes

How to plan when actions do not reliably do what you intend: states, transition models, rewards and discounting, the Bellman equation, and value iteration worked numerically to its fixed point.

Reinforcement LearningProbabilityArtificial Intelligence