A Reinforcement Learning Decentralized Multi-Agent Control Approach exploiting Cognitive Cooperation on Continuous Environments.
Gerardo Camacho-GonzalezSalvatore D'AvellaCarlo Alberto AvizzanoPaolo TripicchioPublished in: CASE (2022)
Keyphrases
- multi agent
- reinforcement learning
- cooperative
- control problems
- multi agent environments
- multi agent systems
- single agent
- robotic systems
- intelligent agents
- multi agent reinforcement learning
- control system
- function approximation
- continuous state spaces
- cognitive agents
- optimal control
- action space
- robot control
- multiagent reinforcement learning
- adaptive control
- control strategies
- learning agents
- multiagent systems
- continuous state and action spaces
- adjustable autonomy
- agent cooperation
- machine learning
- software agents
- cognitive processes
- control strategy
- real world
- state space
- autonomous agents
- cognitive science
- agent behavior
- control method
- control policy
- autonomous robots
- complex environments
- coalition formation
- optimal policy
- peer to peer
- reinforcement learning algorithms
- human operators