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ATAL
2008
Springer
13 years 9 months ago
Not all agents are equal: scaling up distributed POMDPs for agent networks
Many applications of networks of agents, including mobile sensor networks, unmanned air vehicles, autonomous underwater vehicles, involve 100s of agents acting collaboratively und...
Janusz Marecki, Tapana Gupta, Pradeep Varakantham,...
ICMLA
2004
13 years 9 months ago
Planning with predictive state representations
Predictive state representation (PSR) models for controlled dynamical systems have recently been proposed as an alternative to traditional models such as partially observable Mark...
Michael R. James, Satinder P. Singh, Michael L. Li...
UAI
2004
13 years 8 months ago
Region-Based Incremental Pruning for POMDPs
We present a major improvement to the incremental pruning algorithm for solving partially observable Markov decision processes. Our technique targets the cross-sum step of the dyn...
Zhengzhu Feng, Shlomo Zilberstein
AI
2006
Springer
13 years 11 months ago
Belief Selection in Point-Based Planning Algorithms for POMDPs
Abstract. Current point-based planning algorithms for solving partially observable Markov decision processes (POMDPs) have demonstrated that a good approximation of the value funct...
Masoumeh T. Izadi, Doina Precup, Danielle Azar
ICTAI
2005
IEEE
14 years 1 months ago
Planning with POMDPs Using a Compact, Logic-Based Representation
Partially Observable Markov Decision Processes (POMDPs) provide a general framework for AI planning, but they lack the structure for representing real world planning problems in a...
Chenggang Wang, James G. Schmolze