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Comparing Standard with Multiagent Rollout/Policy Iteration
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Classroom Contents
Multiagent Reinforcement Learning: Rollout and Policy Iteration
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- 1 Sources
- 2 Multiagent Problems - A Very Old (19608) and Well-Researched Field
- 3 For this Talk we Focus on Finite-State Intinite Horizon Problems
- 4 Policy Iteration (PI) Algorithm
- 5 Outline of Our Approach for Multiagent Problems
- 6 Underlying Theory: Trading off Control and State Complexity (NDP book, 1996)
- 7 Comparing Standard with Multiagent Rollout/Policy Iteration
- 8 Approximate Policy Iteration with Agent-by-Agent Policy Improvement
- 9 Concluding Remarks
