Learning for Decentralized Control of Multiagent Systems in Large, Partially-Observable Stochastic Environments | Zendy

Miao Liu | Zendy; Christopher Amato | Zendy; Emily Anesta | Zendy; John Griffith | Zendy; Jonathan P. How | Zendy

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Learning for Decentralized Control of Multiagent Systems in Large, Partially-Observable Stochastic Environments

Author(s) -

Miao Liu,

Christopher Amato,

Emily Anesta,

John Griffith,

Jonathan P. How

Publication year - 2016

Publication title -

proceedings of the aaai conference on artificial intelligence

Language(s) - English

Resource type - Journals

eISSN - 2374-3468

pISSN - 2159-5399

DOI - 10.1609/aaai.v30i1.10135

Subject(s) - computer science , reinforcement learning , markov decision process , partially observable markov decision process , scalability , a priori and a posteriori , macro , observable , action (physics) , convergence (economics) , artificial intelligence , control (management) , mathematical optimization , markov process , machine learning , markov chain , markov model , mathematics , philosophy , statistics , physics , economic growth , epistemology , quantum mechanics , database , programming language , economics

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