Scalable Deep Reinforcement Learning Algorithms for Mean Field Games.
Mathieu LaurièreSarah PerrinSertan GirginPaul MullerAyush JainTheophile CabannesGeorgios PiliourasJulien PérolatRomuald ElieOlivier PietquinMatthieu GeistPublished in: ICML (2022)
Keyphrases
- reinforcement learning algorithms
- stochastic games
- reinforcement learning
- model free
- state space
- markov decision processes
- reinforcement learning problems
- learning algorithm
- temporal difference
- eligibility traces
- reinforcement learning methods
- function approximation
- nash equilibria
- markov random field
- multiagent reinforcement learning
- dynamic environments
- game theory
- em algorithm
- policy search
- fixed point
- nash equilibrium
- game playing
- reward function
- markov decision process
- artificial neural networks
- neural network