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» Finding Structure in Reinforcement Learning
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146
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ICML
2005
IEEE
16 years 4 months ago
Clustering through ranking on manifolds
Clustering aims to find useful hidden structures in data. In this paper we present a new clustering algorithm that builds upon the consistency method (Zhou, et.al., 2003), a semi-...
Markus Breitenbach, Gregory Z. Grudic
150
Voted
EGICE
2006
15 years 7 months ago
Evolutionary Generation of Implicative Fuzzy Rules for Design Knowledge Representation
Abstract. In knowledge representation by fuzzy rule based systems two reasoning mechanisms can be distinguished: conjunction-based and implication-based inference. Both approaches ...
Mark Freischlad, Martina Schnellenbach-Held, Torbe...
138
Voted
ATAL
2009
Springer
15 years 10 months ago
Integrating organizational control into multi-agent learning
Multi-Agent Reinforcement Learning (MARL) algorithms suffer from slow convergence and even divergence, especially in largescale systems. In this work, we develop an organization-b...
Chongjie Zhang, Sherief Abdallah, Victor R. Lesser
143
Voted
ALT
2003
Springer
15 years 7 months ago
Efficient Learning of Ordered and Unordered Tree Patterns with Contractible Variables
Due to the rapid growth of tree structured data such as Web documents, efficient learning from tree structured data becomes more and more important. In order to represent structura...
Yusuke Suzuki, Takayoshi Shoudai, Satoshi Matsumot...
107
Voted
HICSS
2006
IEEE
160views Biometrics» more  HICSS 2006»
15 years 9 months ago
A Case Study of a Longstanding Online Community of Practice Involving Critical Care and Advanced Practice Nurses
The aims of this study are: (1) to examine to what extent critical care and advanced practice nurses’ participation in an online listserv constituted a community of practice, an...
Noriko Hara, Khe Foon Hew