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JACM
2006
99views more  JACM 2006»
14 years 10 months ago
Finding a maximum likelihood tree is hard
Abstract. Maximum likelihood (ML) is an increasingly popular optimality criterion for selecting evolutionary trees [Felsenstein 1981]. Finding optimal ML trees appears to be a very...
Benny Chor, Tamir Tuller
GECCO
2007
Springer
183views Optimization» more  GECCO 2007»
15 years 1 months ago
Evolving distributed agents for managing air traffic
Air traffic management offers an intriguing real world challenge to designing large scale distributed systems using evolutionary computation. The ability to evolve effective air t...
Adrian K. Agogino, Kagan Tumer
IJCAI
1997
14 years 11 months ago
Mini-Buckets: A General Scheme for Generating Approximations in Automated Reasoning
The class of algorithms for approximating reasoning tasks presented in this paper is based on approximating the general bucket elimination framework. The algorithms have adjustabl...
Rina Dechter
DAMAS
2005
Springer
15 years 3 months ago
Cognitive Agents for Sense and Respond Logistics
We present a novel cognitive agent architecture and demonstrate its effectiveness in the Sense and Respond Logistics (SRL) domain. Effective applications to support SRL must antic...
Kshanti A. Greene, David G. Cooper, Anna L. Buczak...
GECCO
2008
Springer
186views Optimization» more  GECCO 2008»
14 years 11 months ago
A pareto following variation operator for fast-converging multiobjective evolutionary algorithms
One of the major difficulties when applying Multiobjective Evolutionary Algorithms (MOEA) to real world problems is the large number of objective function evaluations. Approximate...
A. K. M. Khaled Ahsan Talukder, Michael Kirley, Ra...