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AIPS
2009
13 years 9 months ago
Incremental Policy Generation for Finite-Horizon DEC-POMDPs
Solving multiagent planning problems modeled as DECPOMDPs is an important challenge. These models are often solved by using dynamic programming, but the high resource usage of cur...
Christopher Amato, Jilles Steeve Dibangoye, Shlomo...
ECML
2005
Springer
14 years 1 months ago
Active Learning in Partially Observable Markov Decision Processes
This paper examines the problem of finding an optimal policy for a Partially Observable Markov Decision Process (POMDP) when the model is not known or is only poorly specified. W...
Robin Jaulmes, Joelle Pineau, Doina Precup
CIIA
2009
13 years 9 months ago
Dynamic Scheduling in Petroleum Process using Reinforcement Learning
Petroleum industry production systems are highly automatized. In this industry, all functions (e.g., planning, scheduling and maintenance) are automated and in order to remain comp...
Nassima Aissani, Bouziane Beldjilali
EVOW
2009
Springer
14 years 2 months ago
A Hybrid Algorithm for Computing Tours in a Spare Parts Warehouse
We consider a real-world problem arising in a warehouse for spare parts. Items ordered by customers shall be collected and for this purpose our task is to determine efficient picku...
Matthias Prandtstetter, Günther R. Raidl, Tho...
WDAG
2007
Springer
97views Algorithms» more  WDAG 2007»
14 years 2 months ago
On the Message Complexity of Indulgent Consensus
Many recommend planning for the worst and hoping for the best. In this paper we devise efficient indulgent consensus algorithms that can tolerate crash failures and arbitrarily lo...
Seth Gilbert, Rachid Guerraoui, Dariusz R. Kowalsk...