Progress in Evolutionary Computation: AI '93 and AI '94 Workshops on Evolutionary Computation, Melbourne, Victoria, Australia, November 16, 1993, Armidale, NSW, Australia, November 21-22, 1994. Selected PapersXin Yao This volume contains the best carefully revised full papers selected from the presentations accepted for the AI '93 and AI '94 Workshop on Evolutionary Computation held in Australia. The 21 papers included cover a wide range of topics in the field of evolutionary computation, from constrained function optimization to combinatorial optimization, from evolutionary programming to genetic programming, from robotic strategy learning to co-evolutionary game strategy learning. The papers reflect important recent progress in the field; more than half of the papers come from overseas. |
Contents
The Effect of Function Noise on GP Efficiency | 1 |
Genetic Approaches to Learning Recursive Relations | 17 |
An Application of Genetic Programming to the 4Op Problem using MapTrees | 28 |
Direct Replacement A Genetic Algorithm Without Mutation Which Avoids Deception | 41 |
Competitive evolution A Natural Approach to Operator Selection | 49 |
Emergent Collective Computational Abilities in Interacting Particle Systems | 61 |
A Perspective on Evolutionary Computation | 73 |
An Experimental Study of NPerson Iterated Prisoners Dilemma Games | 90 |
Genetic Algorithms for Cutting Stock Problems with and without Contiguity | 166 |
GASBOR A Genetic Algorithm for Switchbox Routing in Integrated Circuits | 187 |
The Calculus of SelfModifiable Algorithm Based Evolutionary Computer Network Routing | 201 |
Evolving Robot Strategy for Open ended Game | 225 |
An Evolutionary Approach to Adaptive ModelBuilding | 236 |
Training Neural Networks With Influence Diagrams | 245 |
A Behavioural Theory of Intelligent Machines as a Framework for the Analysis of Adaptation | 257 |
On Evolving Robust Strategies for Iterated Prisoners Dilemma | 276 |
A Systolic Architecture for High Speed Hypergraph Partitioning Using a Genetic Algorithm | 109 |
Development of Hybrid Optimisation Techniques Based on Genetic Algorithms and Simulated Annealing | 127 |
Development of Parallel Hybrid Optimisation Techniques Based on Genetic Algorithms and Simulated Annealing | 155 |
Comparison of Heuristic Search Algorithms for Single Machine Scheduling Problems | 293 |
Encoding graphs for genetic algorithms An investigation using the minimum spanning tree problem | 305 |
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Progress in Evolutionary Computation: AI '93 and AI '94 Workshops on ... Xin Yao No preview available - 2014 |
Common terms and phrases
11 Wastage 13 Open 25 Open 2nd day 1st 2nd int adaptive application approach average behavioural binary bit string constraints contiguity convergence cooperation cost crossover and mutation crossover operator cutting stock problem day 1st int defined entropy evaluation evolution evolutionary algorithm evolutionary computation evolved example fitness value function GAA2 genes Genetic Algorithms genetic operators Genetic Programming genotype graph heuristics IEEE implementation individual inference engine Influence Diagrams initial population input interacting particle system iterated prisoner's dilemma Koza machine learning method mutation operator neural networks node noise level opponents optimal optimisation optimum parallel parameters parents parse trees particle system performance players Proceedings processors randomly recursive replacement represent representation robot routing runs scheduling search space selection simulated annealing solve steps stock length strategies structure switchbox systolic array tabu search techniques variables