Policy Revision Dynamics and Algorithm Design in Stochastic and Mean-Field Games

Policy Revision Dynamics and Algorithm Design in Stochastic and Mean-Field Games

GERAD Research Center via YouTube Direct link

Decoupling Learning and Adaptation

11 of 13

11 of 13

Decoupling Learning and Adaptation

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Classroom Contents

Policy Revision Dynamics and Algorithm Design in Stochastic and Mean-Field Games

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  1. 1 Intro
  2. 2 Single-Agent Reinforcement Learning
  3. 3 Applications of Multi-Agent Systems
  4. 4 Stochastic Games: Description of Play
  5. 5 Policies (General Treatment)
  6. 6 Objective Functions
  7. 7 Policy Update Rules and Policy Dynamics
  8. 8 e-Satisficing: Definitions
  9. 9 Two-Player Games and e-Satisficing: proof sketch (ctd)
  10. 10 Quantization of Policy Sets
  11. 11 Decoupling Learning and Adaptation
  12. 12 Algorithm for Symmetric Games: Abridged Algorithm
  13. 13 Simulations

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