Imagination-Augmented Agents for Deep Reinforcement Learning.
Sébastien RacanièreTheophane WeberDavid P. ReichertLars BuesingArthur GuezDanilo Jimenez RezendeAdrià Puigdomènech BadiaOriol VinyalsNicolas HeessYujia LiRazvan PascanuPeter W. BattagliaDemis HassabisDavid SilverDaan WierstraPublished in: NIPS (2017)
Keyphrases
- reinforcement learning
- multi agent
- learning agents
- action selection
- multi agent systems
- multiagent systems
- multi agent environments
- single agent
- agent receives
- autonomous agents
- cooperative
- software agents
- learning agent
- multiple agents
- multiagent learning
- reactive agents
- multi agent reinforcement learning
- learning capabilities
- agent technology
- function approximation
- interacting agents
- reinforcement learning agents
- mobile agents
- intelligent agents
- agent behavior
- decision making
- agent systems
- machine learning
- game theoretic
- coalition formation
- resource allocation
- agent architecture
- markov decision processes
- mechanism design
- reinforcement learning algorithms
- reasoning process
- state space
- partial observability
- decentralized control
- optimal policy
- robocup soccer
- dynamic environments
- multiagent reinforcement learning
- learning algorithm
- evolutionary learning
- complex environments
- preference elicitation
- function approximators
- temporal difference