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GECCO
2000
Springer
104views Optimization» more  GECCO 2000»
13 years 8 months ago
Quadratic Bloat in Genetic Programming
In earlier work we predicted program size would grow in the limit at a quadratic rate and up to fty generations we measured bloat O(generations1:2;1:5). On two simple benchmarks w...
William B. Langdon
GECCO
2000
Springer
13 years 8 months ago
Genetic Programming within a Framework of Computer-Aided Discovery of Scientific Knowledge
Present day instrumentation networks already provide immense quantities of data, very little of which provides any insights into the basic physical phenomena that are occurring in...
Maarten Keijzer, Vladan Babovic
GECCO
2000
Springer
225views Optimization» more  GECCO 2000»
13 years 8 months ago
Solving Large Binary Quadratic Programming Problems by Effective Genetic Local Search Algorithm
A genetic local search (GLS) algorithm, which is a combination technique of genetic algorithm and local search, for the unconstrained binary quadratic programming problem (BQP) is...
Kengo Katayama, Masafumi Tani, Hiroyuki Narihisa
GECCO
2000
Springer
112views Optimization» more  GECCO 2000»
13 years 8 months ago
Linguistic Rule Extraction by Genetics-Based Machine Learning
This paper shows how linguistic classification knowledge can be extracted from numerical data for pattern classification problems with many continuous attributes by genetic algori...
Hisao Ishibuchi, Tomoharu Nakashima
GECCO
2000
Springer
142views Optimization» more  GECCO 2000»
13 years 8 months ago
Controlling Effective Introns for Multi-Agent Learning by Genetic Programming
This paper presents the emergence of the cooperative behavior for multiple agents by means of Genetic Programming (GP). For the purpose of evolving the effective cooperative behav...
Hitoshi Iba, Makoto Terao
GECCO
2000
Springer
182views Optimization» more  GECCO 2000»
13 years 8 months ago
A Novel Evolvable Hardware Framework for the Evolution of High Performance Digital Circuits
This paper presents a novel evolvable hardware framework for the automated design of digital circuits for high performance applications. The technique evolves circuits correspondi...
Ben I. Hounsell, Tughrul Arslan
GECCO
2000
Springer
101views Optimization» more  GECCO 2000»
13 years 8 months ago
Polynomial Time Summary Statistics for Two general Classes of Functions
In previous work we showed, by Walsh analysis, that summary statistics such as mean, variance, skew, and higher order statistics can be computed in polynomial time for embedded la...
Robert B. Heckendorn
GECCO
2000
Springer
142views Optimization» more  GECCO 2000»
13 years 8 months ago
Improving EAs for Sequencing Problems
Sequencing problems have to be solved very often in VLSI CAD. To obtain results of high quality, Evolutionary Algorithms (EAs) have been successfully applied in many cases. Howeve...
Wolfgang Günther, Rolf Drechsler
GECCO
2000
Springer
113views Optimization» more  GECCO 2000»
13 years 8 months ago
A Non-Linear Schema Theorem for Genetic Algorithms
We generalize Holland's Schema Theorem to the setting that genes are arranged, not necessarily in a linear sequence, but as the nodes in a connected graph. We have experiment...
William A. Greene