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» Learning Causal Models of Relational Domains
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127
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ATAL
2009
Springer
15 years 1 months ago
Learning to Locate Trading Partners in Agent Networks
This paper is motivated by some recent, intriguing research results involving agent-organized networks (AONs). In AONs, nodes represent agents, and collaboration between nodes are...
John Porter, Kuheli Chakraborty, Sandip Sen
140
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NIPS
2000
15 years 5 months ago
Discovering Hidden Variables: A Structure-Based Approach
A serious problem in learning probabilistic models is the presence of hidden variables. These variables are not observed, yet interact with several of the observed variables. As s...
Gal Elidan, Noam Lotner, Nir Friedman, Daphne Koll...
163
Voted
IJIIDS
2008
201views more  IJIIDS 2008»
15 years 3 months ago
MALEF: Framework for distributed machine learning and data mining
: Growing importance of distributed data mining techniques has recently attracted attention of researchers in multiagent domain. Several agent-based application have been already c...
Jan Tozicka, Michael Rovatsos, Michal Pechoucek, S...
129
Voted
ATAL
2010
Springer
15 years 4 months ago
Frequency adjusted multi-agent Q-learning
Multi-agent learning is a crucial method to control or find solutions for systems, in which more than one entity needs to be adaptive. In today's interconnected world, such s...
Michael Kaisers, Karl Tuyls
186
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COLT
1994
Springer
15 years 7 months ago
Bayesian Inductive Logic Programming
Inductive Logic Programming (ILP) involves the construction of first-order definite clause theories from examples and background knowledge. Unlike both traditional Machine Learnin...
Stephen Muggleton