Publications• Sorted by Date • Classified by Publication Type • Classified by Research Category • Q-value Heuristics for Approximate Solutions of Dec-POMDPsFrans A. Oliehoek and Nikos Vlassis. Q-value Heuristics for Approximate Solutions of Dec-POMDPs. In Proc. of the AAAI spring symposium on Game Theoretic and Decision Theoretic Agents, pp. 31–37, March 2007. DownloadAbstractThe Dec-POMDP is a model for multi-agent planning under uncertainty that has received increasingly more attention over the recent years. In this work we propose a new heuristic QBG that can be used in various algorithms for Dec-POMDPs and describe differences and similarities with QMDP and QPOMDP. An experimental evaluation shows that, at the price of some computation, QBG gives a consistently tighter upper bound to the maximum value obtainable. BibTeX Entry@InProceedings{Oliehoek07GTDTA, author = {Frans A. Oliehoek and Nikos Vlassis}, title = {Q-value Heuristics for Approximate Solutions of Dec-{POMDP}s}, booktitle = {Proc. of the {AAAI} spring symposium on Game Theoretic and Decision Theoretic Agents}, month = mar, year = 2007, pages = {31--37}, note = {}, abstract = { The Dec-POMDP is a model for multi-agent planning under uncertainty that has received increasingly more attention over the recent years. In this work we propose a new heuristic QBG that can be used in various algorithms for Dec-POMDPs and describe differences and similarities with QMDP and QPOMDP. An experimental evaluation shows that, at the price of some computation, QBG gives a consistently tighter upper bound to the maximum value obtainable.} }
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