Progress in Evolutionary Computation

1. Front Matter

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2. The effect of function noise on GP efficiency

   • Jack Y. B. Lee, P. C. Wong

   Pages 1-16

3. Genetic approaches to learning recursive relations

   • P. A. Whigham, R. I. McKay

   Pages 17-27

4. An application of Genetic Programming to the 4-Op problem using map-trees

   • Tevfik Aytekin, E. Erkan Korkmaz, H. Altay Güvenir

   Pages 28-40

5. Direct replacement: A Genetic Algorithm without mutation which avoids deception

   • Jon Rowe, Ian East

   Pages 41-48

6. Competitive evolution: A natural approach to operator selection

   • Q. Tuan Pham

   Pages 49-60

7. Emergent collective computational abilities in interacting particle systems

   • Zhong Zhang, Shuo Bai, Guojie Li

   Pages 61-72

8. A perspective on evolutionary computation

   • Zbigniew Michalewicz

   Pages 73-89

9. An experimental study of N-Person Iterated Prisoner's Dilemma games

   • Xin Yao, Paul J. Darwen

   Pages 90-108

10. A systolic architecture for high speed hypergraph partitioning using a genetic algorithm

    • Heming Chan, Pinaki Mazumder

    Pages 109-126

11. Development of hybrid optimisation techniques based on genetic algorithms and simulated annealing

    • Kit Po Wong, Yin Wa Wong

    Pages 127-154

12. Development of parallel hybrid optimisation techniques based on genetic algorithms and simulated annealing

    • Kit Po Wong, Yin Wa Wong

    Pages 155-165

13. Genetic algorithms for cutting stock problems: With and without contiguity

    • Robert Hinterding, Lutfar Khan

    Pages 166-186

14. GASBOR: A genetic algorithm for switchbox routing in integrated circuits

    • Jens Lienig, K. Thulasiraman

    Pages 187-200

15. The calculus of self-modifiable algorithm based evolutionary computer network routing

    • Davika Seunarine, Eugeniusz Eberbach

    Pages 201-224

16. Evolving robot strategy for open ended game

    • Tomonori Sugiyama, Takashi Kido, Masakazu Nakanishi

    Pages 225-235

17. An evolutionary approach to adaptive model-building

    • Zhengjun Pan, Lishan Kang, Jun He, Yong Liu

    Pages 236-244

18. Training neural networks with influence diagrams

    • Alexei Manso CorrÊa Machado, Mário Fernando Montenegro Campos

    Pages 245-256

19. A behavioural theory of intelligent machines as a framework for the analysis of adaptation

    • Craig A. Lindley

    Pages 257-275

20. On evolving robust strategies for iterated prisoner's dilemma

    • P. J. Darwen, X. Yao

    Pages 276-292

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.

• artificial intelligence
• combinatorial optimization
• evolution
• evolutionary computation
• genetic programming
• learning
• optimization
• programming
• robot
• combinatorics

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