Improving Coordination in Multi-Agent Deep Reinforcement Learning through Memory-driven Communication.
Emanuele PesceGiovanni MontanaPublished in: CoRR (2019)
Keyphrases
- multi agent
- reinforcement learning
- agent communication
- multi agent reinforcement learning
- cooperative multi agent systems
- multiple agents
- multi agent systems
- multiagent systems
- distributed control
- multi agent coordination
- cooperative
- multi agent environments
- multiagent learning
- function approximation
- agent interactions
- single agent
- communication networks
- multi agent planning
- information exchange
- interaction protocols
- intelligent agents
- state space
- reinforcement learning algorithms
- model free
- temporal difference
- data driven
- autonomous agents
- information sharing
- communication systems
- learning algorithm
- coalition formation
- software agents
- heterogeneous agents
- cooperating agents
- memory requirements
- decentralized control
- memory usage
- multi agent learning
- machine learning
- learning agents
- function approximators