Fuzzy Q-Learning Based Multi-Agent System for Intelligent Traffic Control by a Game Theory Approach.
Abolghasem DaeichianAmir HaghaniPublished in: CoRR (2019)
Keyphrases
- game theory
- traffic control
- multi agent systems
- cooperative
- neural networks and genetic algorithms
- traffic signal
- multi agent
- fuzzy logic
- game theoretic
- multi agent learning
- agent technology
- network management
- multi agent reinforcement learning
- nash equilibrium
- single agent
- fuzzy sets
- mechanism design
- fictitious play
- traffic light
- network flow
- nash equilibria
- autonomous agents
- reinforcement learning
- statistical physics
- multi agent cooperation
- software agents
- membership functions
- solution concepts
- intelligent agents
- intelligent systems
- state space
- artificial intelligence
- learning algorithm
- intelligent control
- fuzzy rules
- multiagent learning
- resource allocation
- worst case