Approximating Nash equilibrium for anti-UAV jamming Markov game using a novel event-triggered multi-agent reinforcement learning.
Zikai FengMengxing HuangYuanyuan WuDi WuJinde CaoIakov KorovinSergey GorbachevNadezhda GorbachevaPublished in: Neural Networks (2023)
Keyphrases
- nash equilibrium
- multi agent reinforcement learning
- stochastic games
- game theory
- multi agent learning
- nash equilibria
- game theoretic
- pure strategy
- multi agent systems
- solution concepts
- markov chain
- fictitious play
- mixed strategy
- stackelberg game
- path planning
- repeated games
- equilibrium strategies
- regret minimization
- imperfect information
- learning agents
- worst case
- machine learning
- reinforcement learning
- multiagent learning
- incomplete information
- markov decision processes
- resource allocation
- multi agent