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» Adapting binary fitness functions in Genetic Algorithms
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GECCO
2004
Springer
105views Optimization» more  GECCO 2004»
14 years 4 months ago
Evolution-Based Deliberative Planning for Cooperating Unmanned Ground Vehicles in a Dynamic Environment
Many challenges remain in the development of tactical planning systems that will enable automated, cooperative replanning of routes and mission assignments for multiple unmanned gr...
Talib S. Hussain, David J. Montana, Gordon Vidaver
CEC
2010
IEEE
13 years 12 months ago
Improving GP classification performance by injection of decision trees
This paper presents a novel hybrid method combining genetic programming and decision tree learning. The method starts by estimating a benchmark level of reasonable accuracy, based ...
Rikard König, Ulf Johansson, Tuve Löfstr...
CEC
2005
IEEE
14 years 4 months ago
A quantitative approach for validating the building-block hypothesis
The building blocks are common structures of high-quality solutions. Genetic algorithms often assume the building-block hypothesis. It is hypothesized that the high-quality solutio...
Chatchawit Aporntewan, Prabhas Chongstitvatana
PDCN
2007
14 years 6 days ago
Design and evaluation of an auto-memoization processor
This paper describes the design and evaluation of an auto-memoization processor. The major point of this proposal is to detect the multilevel functions and loops with no additiona...
Tomoaki Tsumura, Ikuma Suzuki, Yasuki Ikeuchi, Hir...
STOC
2004
ACM
150views Algorithms» more  STOC 2004»
14 years 11 months ago
Typical properties of winners and losers in discrete optimization
We present a probabilistic analysis for a large class of combinatorial optimization problems containing, e.g., all binary optimization problems defined by linear constraints and a...
René Beier, Berthold Vöcking