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TACAS
2009
Springer
89views Algorithms» more  TACAS 2009»
14 years 2 months ago
Hierarchical Adaptive State Space Caching Based on Level Sampling
In the past, several attempts have been made to deal with the state space explosion problem by equipping a depth-first search (DFS) algorithm with a state cache, or by avoiding co...
Radu Mateescu, Anton Wijs
ICDM
2008
IEEE
230views Data Mining» more  ICDM 2008»
14 years 1 months ago
Evolutionary Clustering by Hierarchical Dirichlet Process with Hidden Markov State
This paper studies evolutionary clustering, which is a recently hot topic with many important applications, noticeably in social network analysis. In this paper, based on the rece...
Tianbing Xu, Zhongfei (Mark) Zhang, Philip S. Yu, ...
PRICAI
2000
Springer
13 years 11 months ago
Generating Hierarchical Structure in Reinforcement Learning from State Variables
This paper presents the CQ algorithm which decomposes and solves a Markov Decision Process (MDP) by automatically generating a hierarchy of smaller MDPs using state variables. The ...
Bernhard Hengst
FLAIRS
2004
13 years 8 months ago
State Space Reduction For Hierarchical Reinforcement Learning
er provides new techniques for abstracting the state space of a Markov Decision Process (MDP). These techniques extend one of the recent minimization models, known as -reduction, ...
Mehran Asadi, Manfred Huber
AAAI
1996
13 years 8 months ago
Building Steady-State Simulators via Hierarchical Feedback Decomposition
In recent years, compositional modeling and selfexplanatory simulation techniques have simplified the process of building dynamic simulators of physical systems. Building steady-s...
Nicolas F. Rouquette