A game-theoretic analysis of networked system control for common-pool resource management using multi-agent reinforcement learning.
Arnu PretoriusScott CameronElan Van BiljonTom MakkinkShahil MawjeeJeremy du PlessisJonathan ShockAlexandre LaterreKarim BeguirPublished in: NeurIPS (2020)
Keyphrases
- resource management
- theoretic analysis
- multi agent reinforcement learning
- management system
- stochastic games
- distributed control
- resource allocation
- intelligent agents
- control system
- quality of service
- resource utilization
- multi agent
- game theory
- resource usage
- computer games
- video games
- learning agents
- control strategy
- game theoretic
- multi agent systems
- nash equilibrium
- multi agent learning
- response time
- computational intelligence