Today within the multiagent community, we see at least four competing methods to building multiagent systems: beliefdesireintention (BDI), distributed constraint optimization (DCOP), distributed POMDPs, and auctions or game-theoretic methods. While there is exciting progress within each approach, there is a lack of cross-cutting research. This article highlights the various hybrid techniques for multiagent teamwork developed by the teamcore group. In particular, for the past decade, the TEAMCORE research group has focused on building agent teams in complex, dynamic domains. While our early work was inspired by BDI, we will present an overview of recent research that uses DCOPs and distributed POMDPs in building agent teams. While DCOP and distributed POMDP algorithms provide promising results, hybrid approaches allow us to use the complementary strengths of different techniques to create algorithms that perform better than either of their component algorithms alone. For example, in the BDI-POMDP hybrid approach, BDI team plans are exploited to improve POMDP tractability, and POMDPs improve BDI team plan performance.
Artificial Intelligence and Robotics | Business | Operations Research, Systems Engineering and Industrial Engineering
Intelligent Systems and Decision Analytics
Computer Society of India
PARUCHURI, Praveen; Bowring, Emma; Nair, Ranjit; Pearce, Jonathan; Schurr, Nathan; Tambe, Milind; and VARAKANTHAM, Pradeep.
Multiagent Teamwork: Hybrid Approaches. (2006). CSI Communications. 19-24. Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/995
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