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ICML
1995
IEEE
14 years 10 months ago
Stable Function Approximation in Dynamic Programming
The success ofreinforcement learninginpractical problems depends on the ability to combine function approximation with temporal di erence methods such as value iteration. Experime...
Geoffrey J. Gordon
ECAI
2006
Springer
14 years 1 months ago
An Efficient Upper Approximation for Conditional Preference
The fundamental operation of dominance testing, i.e., determining if one alternative is preferred to another, is in general very hard for methods of reasoning with qualitative cond...
Nic Wilson
CAD
2008
Springer
13 years 10 months ago
Approximate computation of curves on B-spline surfaces
Curves on surfaces play an important role in computer-aided geometric design. Because of the considerably high degree of exact curves on surfaces, approximation algorithms are pre...
Yi-Jun Yang, Song Cao, Jun-Hai Yong, Hui Zhang, Je...
LICS
2009
IEEE
14 years 4 months ago
Clipping: A Semantics-Directed Syntactic Approximation
In this paper we introduce “clipping,” a new method of syntactic approximation which is motivated by and works in conjunction with a sound and decidable denotational model for...
Dan R. Ghica, Adam Bakewell
ICML
2009
IEEE
14 years 10 months ago
Constraint relaxation in approximate linear programs
Approximate Linear Programming (ALP) is a reinforcement learning technique with nice theoretical properties, but it often performs poorly in practice. We identify some reasons for...
Marek Petrik, Shlomo Zilberstein