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GECCO
2000
Springer
114views Optimization» more  GECCO 2000»
14 years 3 months ago
Intelligent Recombination Using Individual Learning in a Collective Learning Genetic Algorithm
This paper introduces a new collective learning genetic algorithm (CLGA) which employs individual learning to do intelligent recombination based on a cooperative exchange of knowl...
Terry P. Riopka, Peter Bock
GECCO
2000
Springer
121views Optimization» more  GECCO 2000»
14 years 3 months ago
Informed operators: Speeding up genetic-algorithm-based design optimization using reduced models
In this paper we describe a method for improving genetic-algorithm-based optimization using informed genetic operators. The idea is to make the genetic operators such as mutation ...
Khaled Rasheed, Haym Hirsh
GECCO
2000
Springer
109views Optimization» more  GECCO 2000»
14 years 3 months ago
GP+Echo+Subsumption = Improved Problem Solving
Real-time, adaptive control is a difficult problem that can be addressed by EC architectures. We are interested in incorporating into an EC architecture some of the features that ...
William F. Punch, W. M. Rand
GECCO
2000
Springer
117views Optimization» more  GECCO 2000»
14 years 3 months ago
Exact Schema Theorem and Effective Fitness for GP with One-Point Crossover
This paper extends recent results in the GP schema theory by formulating a proper exact schema theorem for GP with one-point crossover. This gives an exact expression for the expe...
Riccardo Poli
GECCO
2000
Springer
108views Optimization» more  GECCO 2000»
14 years 3 months ago
Hierarchical Problem Solving and the Bayesian Optimization Algorithm
The paper discusses three major issues. First, it discusses why it makes sense to approach problems in a hierarchical fashion. It de nes the class of hierarchically decomposable f...
Martin Pelikan, David E. Goldberg
GECCO
2000
Springer
143views Optimization» more  GECCO 2000»
14 years 3 months ago
A Genetic Algorithm for Automatically Designing Modular Reinforcement Learning Agents
Reinforcement learning (RL) is one of the machine learning techniques and has been received much attention as a new self-adaptive controller for various systems. The RL agent auto...
Isao Ono, Tetsuo Nijo, Norihiko Ono
GECCO
2000
Springer
156views Optimization» more  GECCO 2000»
14 years 3 months ago
Optimal Mutation Rates and Selection Pressure in Genetic Algorithms
It has been argued that optimal per-locus mutation rates in GAs are proportional to selection pressure and the reciprocal of genotype length. In this paper we suggest that the not...
Gabriela Ochoa, Inman Harvey, Hilary Buxton
GECCO
2000
Springer
158views Optimization» more  GECCO 2000»
14 years 3 months ago
Grammar based function definition in Grammatical Evolution
We describe the use of grammars as an approach to automatic function definition in Grammatical Evolution. The automatic generation of functions allows the evolution of both the fu...
Michael O'Neill, Conor Ryan
GECCO
2000
Springer
153views Optimization» more  GECCO 2000»
14 years 3 months ago
Applying Genetic Algorithms to Multi-Objective Land Use Planning
This paper explores the application of multiobjective Genetic Algorithms (mGAs) to rural land use planning, a spatial allocation problem. Two mGAs are proposed. Both share an unde...
Keith B. Matthews, Susan Craw, Stewart Elder, Alan...
GECCO
2000
Springer
145views Optimization» more  GECCO 2000»
14 years 3 months ago
A New Genetic Algorithm for Minimum Span Frequency Assignment using Permutation and Clique
We propose a new Genetic Algorithm (GA) for solving the minimum span frequency assignment problem (MSFAP). The MSFAP is minimizing the range of the frequencies assigned to each tr...
Shouichi Matsui, Ken-ichi Tokoro