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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
CPAIOR
2008
Springer
13 years 9 months ago
Amsaa: A Multistep Anticipatory Algorithm for Online Stochastic Combinatorial Optimization
The one-step anticipatory algorithm (1s-AA) is an online algorithm making decisions under uncertainty by ignoring future non-anticipativity constraints. It makes near-optimal decis...
Luc Mercier, Pascal Van Hentenryck
HICSS
2003
IEEE
207views Biometrics» more  HICSS 2003»
14 years 23 days ago
Formalizing Multi-Agent POMDP's in the context of network routing
This paper uses partially observable Markov decision processes (POMDP’s) as a basic framework for MultiAgent planning. We distinguish three perspectives: first one is that of a...
Bharaneedharan Rathnasabapathy, Piotr J. Gmytrasie...
NIPS
2001
13 years 8 months ago
Multiagent Planning with Factored MDPs
We present a principled and efficient planning algorithm for cooperative multiagent dynamic systems. A striking feature of our method is that the coordination and communication be...
Carlos Guestrin, Daphne Koller, Ronald Parr
ICRA
2010
IEEE
163views Robotics» more  ICRA 2010»
13 years 6 months ago
Exploiting domain knowledge in planning for uncertain robot systems modeled as POMDPs
Abstract— We propose a planning algorithm that allows usersupplied domain knowledge to be exploited in the synthesis of information feedback policies for systems modeled as parti...
Salvatore Candido, James C. Davidson, Seth Hutchin...