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» Metaphor for learning: an evolutionary algorithm
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ATAL
2010
Springer
13 years 8 months ago
Evolving policy geometry for scalable multiagent learning
A major challenge for traditional approaches to multiagent learning is to train teams that easily scale to include additional agents. The problem is that such approaches typically...
David B. D'Ambrosio, Joel Lehman, Sebastian Risi, ...
ANOR
2011
175views more  ANOR 2011»
13 years 2 months ago
Integrated exact, hybrid and metaheuristic learning methods for confidentiality protection
A vital task facing government agencies and commercial organizations that report data is to represent the data in a meaningful way and simultaneously to protect the confidentialit...
Fred Glover, Lawrence H. Cox, Rahul Patil, James P...
PLDI
2003
ACM
14 years 28 days ago
Meta optimization: improving compiler heuristics with machine learning
Compiler writers have crafted many heuristics over the years to approximately solve NP-hard problems efficiently. Finding a heuristic that performs well on a broad range of applic...
Mark Stephenson, Saman P. Amarasinghe, Martin C. M...
GECCO
2005
Springer
144views Optimization» more  GECCO 2005»
14 years 1 months ago
Multiobjective hBOA, clustering, and scalability
This paper describes a scalable algorithm for solving multiobjective decomposable problems by combining the hierarchical Bayesian optimization algorithm (hBOA) with the nondominat...
Martin Pelikan, Kumara Sastry, David E. Goldberg
BMCBI
2006
192views more  BMCBI 2006»
13 years 7 months ago
Analysis of circular genome rearrangement by fusions, fissions and block-interchanges
Background: Analysis of genomes evolving via block-interchange events leads to a combinatorial problem of sorting by block-interchanges, which has been studied recently to evaluat...
Chin Lung Lu, Yen-Lin Huang, Tsui Ching Wang, Hsie...