On convergence rates of game theoretic reinforcement learning algorithms.
Zhisheng HuMinghui ZhuPing ChenPeng LiuPublished in: Autom. (2019)
Keyphrases
- game theoretic
- convergence rate
- reinforcement learning algorithms
- reinforcement learning
- game theory
- step size
- state space
- temporal difference
- markov decision processes
- model free
- convergence speed
- learning rate
- decision problems
- function approximation
- learning algorithm
- nash equilibrium
- imperfect information
- cooperative
- solution concepts
- dynamic environments
- trust model
- bayesian networks
- resource allocation
- particle swarm optimization
- cost function
- nash equilibria
- policy iteration
- lower bound