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All Outputs (126)

An examination of tuneable, random search landscapes (1999)
Presentation / Conference
Smith, R., & Smith, J. (1999, June). An examination of tuneable, random search landscapes. Paper presented at Foundations of Genetic Algorithms 5, Morgan Kaufmann, San Francisco, USA

Protein structure prediction with evolutionary algorithms (1999)
Presentation / Conference
Krasnogor, N., Hart, W., Smith, J., & Pelta, D. (1999, June). Protein structure prediction with evolutionary algorithms. Paper presented at Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 1999), Morgan Kaufmann, San Francisco, USA

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.

Genetic selection of features for clustering and classification (1997)
Presentation / Conference
Smith, J., Fogarty, T. C., & Johnson, I. R. (1997, June). Genetic selection of features for clustering and classification. Paper presented at Genetic Algorithms in Image Processing and Vision, IEE Colloquium on, Houston, USA

Operator and parameter adaptation in genetic algorithms (1997)
Journal Article
Smith, J., & Fogarty, T. (1997). Operator and parameter adaptation in genetic algorithms. Soft Computing, 1(2), 81-87. https://doi.org/10.1007/s005000050009

Genetic Algorithms are a class of powerful, robust search techniques based on genetic inheritance and the Darwinian metaphor of “Natural Selection”. These algorithms maintain a finite memory of individual points on the search landscape known as the... Read More about Operator and parameter adaptation in genetic algorithms.

Recombination strategy adaptation via evolution of gene linkage (1996)
Presentation / Conference
Smith, J., & Fogarty, T. (1996, June). Recombination strategy adaptation via evolution of gene linkage. Paper presented at Proceedings of the 1996 IEEE Conference on Evolutionary Computation, IEEE Press, Piscataway, NJ, USA

Visualising state space representations of LSTM networks
Presentation / Conference
Smith, E. M., Smith, J., Legg, P., & Francis, S. Visualising state space representations of LSTM networks. Presented at Workshop on Visualization for AI Explainability, Berlin, Germany

Long Short-Term Memory (LSTM) networks have proven to be one of the most effective models for making predictions on sequence-based tasks. These models work by capturing, remembering, and forgetting information relevant to their future predictions. Th... Read More about Visualising state space representations of LSTM networks.

Credit assignment in adaptive memetic algorithms
Presentation / Conference
Smith, J. Credit assignment in adaptive memetic algorithms. Paper presented at Proceedings of Gecco, the ACM-SIGEVO Conference on Evolutionary Computation, Springer, Berlin, Heidelberg, New York

What have gene libraries done for AIS?
Presentation / Conference
Cayzer, S., Smith, J., Marshall, J., & Kovacs, T. What have gene libraries done for AIS?. Paper presented at Proceedings of ICARIS 2005: 4th International Conference on Artificial Immune Systems, Springer, Berlin, Heidelberg, New York