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206
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WSDM
2010
ACM
322views Data Mining» more  WSDM 2010»
16 years 4 months ago
Inferring Search Behaviors Using Partially Observable Markov (POM) Model
This article describes an application of the partially observable Markov (POM) model to the analysis of a large scale commercial web search log. Mathematically, POM is a variant o...
Kuansan Wang, Nikolas Gloy, Xiaolong Li
178
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ATAL
2008
Springer
15 years 8 months ago
On the usefulness of opponent modeling: the Kuhn Poker case study
The application of reinforcement learning algorithms to Partially Observable Stochastic Games (POSG) is challenging since each agent does not have access to the whole state inform...
Alessandro Lazaric, Mario Quaresimale, Marcello Re...
186
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ICML
2002
IEEE
16 years 7 months ago
Hierarchically Optimal Average Reward Reinforcement Learning
Two notions of optimality have been explored in previous work on hierarchical reinforcement learning (HRL): hierarchical optimality, or the optimal policy in the space defined by ...
Mohammad Ghavamzadeh, Sridhar Mahadevan
SIGMOD
2005
ACM
161views Database» more  SIGMOD 2005»
16 years 7 months ago
Efficient Keyword Search for Smallest LCAs in XML Databases
Keyword search is a proven, user-friendly way to query HTML documents in the World Wide Web. We propose keyword search in XML documents, modeled as labeled trees, and describe cor...
Yu Xu, Yannis Papakonstantinou
ALGORITHMICA
2005
84views more  ALGORITHMICA 2005»
15 years 6 months ago
Optimal Read-Once Parallel Disk Scheduling
An optimal prefetching and I/O scheduling algorithm L-OPT, for parallel I/O systems, using a read-once model of block references is presented. The algorithm uses knowledge of the n...
Mahesh Kallahalla, Peter J. Varman