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122
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ICML
1998
IEEE
16 years 3 months ago
The MAXQ Method for Hierarchical Reinforcement Learning
This paper presents a new approach to hierarchical reinforcement learning based on the MAXQ decomposition of the value function. The MAXQ decomposition has both a procedural seman...
Thomas G. Dietterich
120
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IJCAI
2003
15 years 4 months ago
Optimal Time-Space Tradeoff in Probabilistic Inference
Recursive Conditioning, RC, is an any-space algorithm lor exact inference in Bayesian networks, which can trade space for time in increments of the size of a floating point number...
David Allen, Adnan Darwiche
116
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CEC
2008
IEEE
15 years 9 months ago
A parallel surrogate-assisted multi-objective evolutionary algorithm for computationally expensive optimization problems
Abstract— This paper presents a new efficient multiobjective evolutionary algorithm for solving computationallyintensive optimization problems. To support a high degree of parall...
Anna Syberfeldt, Henrik Grimm, Amos Ng, Robert Ivo...
92
Voted
AAAI
2006
15 years 4 months ago
An Asymptotically Optimal Algorithm for the Max k-Armed Bandit Problem
We present an asymptotically optimal algorithm for the max variant of the k-armed bandit problem. Given a set of k slot machines, each yielding payoff from a fixed (but unknown) d...
Matthew J. Streeter, Stephen F. Smith
114
Voted
COR
2008
111views more  COR 2008»
15 years 2 months ago
An optimization algorithm for the inventory routing problem with continuous moves
The typical inventory routing problem deals with the repeated distribution of a single product from a single facility with an unlimited supply to a set of customers that can all b...
Martin W. P. Savelsbergh, Jin-Hwa Song