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IJCAI
2007
13 years 10 months ago
Using Linear Programming for Bayesian Exploration in Markov Decision Processes
A key problem in reinforcement learning is finding a good balance between the need to explore the environment and the need to gain rewards by exploiting existing knowledge. Much ...
Pablo Samuel Castro, Doina Precup
IJHPCA
2006
109views more  IJHPCA 2006»
13 years 9 months ago
A Resource Leasing Policy for on-Demand Computing
Leasing computational resources for on-demand computing is now a viable option for providers of network services. Temporary spikes or lulls in demand for a service can be accommod...
Darin England, Jon B. Weissman
CLEIEJ
2004
119views more  CLEIEJ 2004»
13 years 9 months ago
Pump Scheduling Optimization Using Asynchronous Parallel
Optimizing the pump-scheduling is an interesting proposal to achieve cost reductions in water distribution pumping stations. As systems grow, pump-scheduling becomes a very diffic...
Christian von Lücken, Benjamín Bar&aac...
JAIR
2000
152views more  JAIR 2000»
13 years 9 months ago
Value-Function Approximations for Partially Observable Markov Decision Processes
Partially observable Markov decision processes (POMDPs) provide an elegant mathematical framework for modeling complex decision and planning problems in stochastic domains in whic...
Milos Hauskrecht
TOG
2002
162views more  TOG 2002»
13 years 9 months ago
Jigsaw image mosaics
This paper introduces a new kind of mosaic, called Jigsaw Image Mosaic (JIM), where image tiles of arbitrary shape are used to compose the final picture. The generation of a Jigsa...
Junhwan Kim, Fabio Pellacini