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Outputs (9)

Self adaptation in evolutionary algorithms (1998)
Thesis
Smith, J. Self adaptation in evolutionary algorithms. (Thesis). University of the West of England. Retrieved from https://uwe-repository.worktribe.com/output/1099661

Evolutionary Algorithms are search algorithms based on the Darwinian metaphor of “Natural Selection”. Typically these algorithms maintain a population of individual solutions, each of which has a fitness attached to it, which in some way reflects the... Read More about Self adaptation in evolutionary algorithms.

A corporate classifier system (1998)
Conference Proceeding
Tomlinson, A., & Bull, L. (1998). A corporate classifier system. In A. E. Eiben, T. Bäck, M. Schoenauer, & H. Schwefel (Eds.), Parallel Problem Solving from Nature—PPSN V. , (550-559). https://doi.org/10.1007/BFb0056897

Based on the proposals of Wilson and Goldberg we introduce a macro-level evolutionary operator which creates structural links between rules in the ZCS model and thus forms "corporations" of rules within the classifier system population. Rule co-depen... Read More about A corporate classifier system.

Self organising maps for the investigation of clinical data: A case study (1998)
Journal Article
Sharpe, P. K., & Caleb-Solly, P. (1998). Self organising maps for the investigation of clinical data: A case study. Neural Computing and Applications, 7(1), 65-70. https://doi.org/10.1007/BF01413710

The clinical process often involves comparisons of how one set of measurements is related to previous, similar, data and the use of this information to take decisions concerning possible courses of action, often with insufficient data to make meaning... Read More about Self organising maps for the investigation of clinical data: A case study.

On ZCS in multi-agent environments (1998)
Conference Proceeding
Bull, L. (1998). On ZCS in multi-agent environments. In A. Eiben, T. Bäck, M. Schoenauer, & H. Schwefel (Eds.), Parallel Problem Solving from Nature—PPSN V. , (471-480). https://doi.org/10.1007/BFb0056889

This paper examines the performance of the ZCS Michigan-style classifier system in multi-agent environments. Using an abstract multi-agent model the effects of varying aspects of the performance, reinforcement and discovery components are examined. I... Read More about On ZCS in multi-agent environments.

Evolutionary computing in multi-agent environments: Operators (1998)
Conference Proceeding
Bull, L. (1998). Evolutionary computing in multi-agent environments: Operators. In V. W. Porto, N. Saravanan, D. Waagen, & A. E. Eiben (Eds.), In EP 1998: Evolutionary Programming VII. , (43-52). https://doi.org/10.1007/BFb0040758

This paper examines a key aspect of applying evolutionary computing techniques to multi-agent systems: a comparison in the performance of the genetic operators of mutation and recombination. Using the tuneable NKC model of multi-agent evolution it is... Read More about Evolutionary computing in multi-agent environments: Operators.

Co-evolving functions in genetic programming: Dynamic ADF creation using GLiB (1998)
Book Chapter
Ahluwalia, M., & Bull, L. (1998). Co-evolving functions in genetic programming: Dynamic ADF creation using GLiB. In W. V. Porto, N. Saravanan, D. E. Waagen, & A. Eiben (Eds.), Proceedings of the 7th International Conference on Evolutionary Programming VII (809-818). London: Springer-Verlag