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EMO
2001
Springer
109views Optimization» more  EMO 2001»
13 years 9 months ago
Specification of Genetic Search Directions in Cellular Multi-objective Genetic Algorithms
When we try to implement a multi-objective genetic algorithm (MOGA) with variable weights for finding a set of Pareto optimal solutions, one difficulty lies in determining appropri...
Tadahiko Murata, Hisao Ishibuchi, Mitsuo Gen
ECAI
2006
Springer
13 years 9 months ago
Random Subset Optimization
Some of the most successful algorithms for satisfiability, such as Walksat, are based on random walks. Similarly, local search algorithms for solving constraint optimization proble...
Boi Faltings, Quang Huy Nguyen
ICML
2001
IEEE
14 years 6 months ago
Direct Policy Search using Paired Statistical Tests
Direct policy search is a practical way to solve reinforcement learning problems involving continuous state and action spaces. The goal becomes finding policy parameters that maxi...
Malcolm J. A. Strens, Andrew W. Moore
ECCC
2011
282views ECommerce» more  ECCC 2011»
12 years 11 months ago
Almost k-wise vs. k-wise independent permutations, and uniformity for general group actions
A family of permutations in Sn is k-wise independent if a uniform permutation chosen from the family maps any distinct k elements to any distinct k elements equally likely. Effici...
Noga Alon, Shachar Lovett
JCO
1998
136views more  JCO 1998»
13 years 5 months ago
A Greedy Randomized Adaptive Search Procedure for the Feedback Vertex Set Problem
Abstract. A Greedy Randomized Adaptive Search Procedure (GRASP) is a randomized heuristic that has produced high quality solutions for a wide range of combinatorial optimization pr...
Panos M. Pardalos, Tianbing Qian, Mauricio G. C. R...