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PPSN
2000
Springer
13 years 11 months ago
Optimizing through Co-evolutionary Avalanches
Abstract. We explore a new general-purpose heuristic for nding highquality solutions to hard optimization problems. The method, called extremal optimization, is inspired by self-or...
Stefan Boettcher, Allon G. Percus, Michelangelo Gr...
AAAI
2000
13 years 9 months ago
Iterative Flattening: A Scalable Method for Solving Multi-Capacity Scheduling Problems
One challenge for research in constraint-based scheduling has been to produce scalable solution procedures under fairly general representational assumptions. Quite often, the comp...
Amedeo Cesta, Angelo Oddi, Stephen F. Smith
JAIR
2008
157views more  JAIR 2008»
13 years 7 months ago
Learning to Reach Agreement in a Continuous Ultimatum Game
It is well-known that acting in an individually rational manner, according to the principles of classical game theory, may lead to sub-optimal solutions in a class of problems nam...
Steven de Jong, Simon Uyttendaele, Karl Tuyls
IJRR
2007
104views more  IJRR 2007»
13 years 7 months ago
Deep Space Formation Flying Spacecraft Path Planning
Efficient algorithms for collision-free energy sub-optimal path planning for formations of spacecraft flying in deep space are presented. The idea is to introduce a set of way-poi...
Cornel Sultan, Sanjeev Seereeram, Raman K. Mehra
TSP
2008
151views more  TSP 2008»
13 years 7 months ago
Reduce and Boost: Recovering Arbitrary Sets of Jointly Sparse Vectors
The rapid developing area of compressed sensing suggests that a sparse vector lying in a high dimensional space can be accurately and efficiently recovered from only a small set of...
Moshe Mishali, Yonina C. Eldar