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AAAI
1998
14 years 11 months ago
Tree Based Discretization for Continuous State Space Reinforcement Learning
Reinforcement learning is an effective technique for learning action policies in discrete stochastic environments, but its efficiency can decay exponentially with the size of the ...
William T. B. Uther, Manuela M. Veloso
FUIN
2008
108views more  FUIN 2008»
14 years 10 months ago
Radial View of Continuous Cellular Automata
Continuous cellular automata (or coupled map lattices) are cellular automata where the state of the cells are real values in [0, 1] and the local transition rule is a real function...
Paola Flocchini, Vladimir Cezar
WAIM
2010
Springer
14 years 7 months ago
Efficient Continuous Top-k Keyword Search in Relational Databases
Keyword search in relational databases has been widely studied in recent years. Most of the previous studies focus on how to answer an instant keyword query. In this paper, we focu...
Yanwei Xu, Yoshiharu Ishikawa, Jihong Guan
GIS
2009
ACM
14 years 7 months ago
Distortion-based anonymity for continuous queries in location-based mobile services
Privacy preservation has recently received considerable attention for location-based mobile services. Various location cloaking approaches have been proposed to protect the locati...
Xiao Pan, Xiaofeng Meng, Jianliang Xu
AAAI
2011
13 years 10 months ago
Combining Learned Discrete and Continuous Action Models
Action modeling is an important skill for agents that must perform tasks in novel domains. Previous work on action modeling has focused on learning STRIPS operators in discrete, r...
Joseph Z. Xu, John E. Laird