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IJCAI
2007
14 years 11 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
AUSAI
1999
Springer
15 years 2 months ago
Generating Rule Sets from Model Trees
Model trees—decision trees with linear models at the leaf nodes—have recently emerged as an accurate method for numeric prediction that produces understandable models. However,...
Geoffrey Holmes, Mark Hall, Eibe Frank
SWAT
2000
Springer
90views Algorithms» more  SWAT 2000»
15 years 1 months ago
Efficient Expected-Case Algorithms for Planar Point Location
Planar point location is among the most fundamental search problems in computational geometry. Although this problem has been heavily studied from the perspective of worst-case que...
Sunil Arya, Siu-Wing Cheng, David M. Mount, Ramesh...
FOCS
2006
IEEE
15 years 3 months ago
Generalization of Binary Search: Searching in Trees and Forest-Like Partial Orders
We extend the binary search technique to searching in trees. We consider two models of queries: questions about vertices and questions about edges. We present a general approach t...
Krzysztof Onak, Pawel Parys
ANOR
2007
165views more  ANOR 2007»
14 years 10 months ago
Financial scenario generation for stochastic multi-stage decision processes as facility location problems
The quality of multi-stage stochastic optimization models as they appear in asset liability management, energy planning, transportation, supply chain management, and other applicat...
Ronald Hochreiter, Georg Ch. Pflug