Achieving Fairness in Multi-Agent MDP Using Reinforcement Learning.
Peizhong JuArnob GhoshNess B. ShroffPublished in: ICLR (2024)
Keyphrases
- reinforcement learning
- multi agent
- markov decision processes
- markov decision process
- optimal policy
- state space
- function approximation
- reinforcement learning algorithms
- action sets
- markov decision problems
- reward function
- learning algorithm
- transfer learning
- state and action spaces
- multiagent systems
- game theory
- model free
- intelligent agents
- partially observable
- partially observable markov decision processes
- multi agent systems
- resource allocation
- state abstraction
- cooperative
- learning agents
- policy iteration
- single agent
- linear programming
- temporal difference
- function approximators
- policy search
- multi agent environments
- traffic signal control
- bayesian reinforcement learning
- control policy
- partial observability
- finite state
- machine learning