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NIPS
1997
13 years 9 months ago
Reinforcement Learning with Hierarchies of Machines
We present a new approach to reinforcement learning in which the policies considered by the learning process are constrained by hierarchies of partially specified machines. This ...
Ronald Parr, Stuart J. Russell
BMCBI
2006
155views more  BMCBI 2006»
13 years 8 months ago
AffyMiner: mining differentially expressed genes and biological knowledge in GeneChip microarray data
Background: DNA microarrays are a powerful tool for monitoring the expression of tens of thousands of genes simultaneously. With the advance of microarray technology, the challeng...
Guoqing Lu, The V. Nguyen, Yuannan Xia, Michael Fr...
OTM
2010
Springer
13 years 6 months ago
A Personalized and Collaborative eLearning Materials Recommendation Scenario Using Ontology-Based Data Matching Strategies
Abstract. We propose a virtual teacher for the evaluation of students’ competencies. It aims to improve learning by making personalized suggestions on the learning materials. It ...
Ioana Ciuciu, Yan Tang
IAT
2008
IEEE
13 years 8 months ago
Cognitive Agents Integrating Rules and Reinforcement Learning for Context-Aware Decision Support
While context-awareness has been found to be effective for decision support in complex domains, most of such decision support systems are hard-coded, incurring significant develop...
Teck-Hou Teng, Ah-Hwee Tan
ATAL
2010
Springer
13 years 9 months ago
Learning multi-agent state space representations
This paper describes an algorithm, called CQ-learning, which learns to adapt the state representation for multi-agent systems in order to coordinate with other agents. We propose ...
Yann-Michaël De Hauwere, Peter Vrancx, Ann No...