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Convex optimization / Dynamic programming / Markov processes / Stochastic control / Lagrangian relaxation / Duality / Markov decision process / Relaxation / Randomized rounding / Mathematical optimization / Statistics / Mathematical analysis


Lagrangian Relaxation for Large-Scale Multi-Agent Planning∗ (Extended Abstract) Geoffrey J. Gordon† , Pradeep Varakantham‡ , William Yeoh‡ , Hoong Chuin Lau‡ , Ajay S. Aravamudhan‡ and Shih-Fen Cheng‡ †
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Document Date: 2012-02-29 09:16:26

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City

Valencia / /

Company

Multiagent Systems / /

Country

Jordan / Spain / /

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Facility

Singapore Management University / International Research Centre / Carnegie Mellon University / /

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ubiquitous computing / feasible solution / near-optimal solutions / near-optimal solution / policy search method / car navigation devices / feasible solutions / heuristic solutions / /

Organization

USA School of Information Systems / Learning Department / IDM Programme Office / Singapore Management University / Singapore / Carnegie Mellon University / Pittsburgh / International Foundation for Autonomous Agents / Singapore National Research Foundation / International Research Centre / /

Person

Shih-Fen Cheng / Paper / Geoffrey J. Gordon / William Yeoh / Ajay S. Aravamudhan / /

Position

Vp / Prime Minister / max Vp / AI General / representative / /

Technology

Dual H=5 Primal H=5 Dual H=7 Primal H=7 Dual H=10 Primal H=10 SLR ALGORITHM / artificial intelligence / mobile phones / Machine Learning / /

URL

www.ifaamas.org / /

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