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
All Outputs (126)
Replacement strategies in steady state genetic algorithms: Static environments (1999)
Presentation / Conference
Smith, J., & Vavak, F. (1999, June). Replacement strategies in steady state genetic algorithms: Static environments. 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
Replacement strategies in steady state genetic algorithms: Dynamic environments (1999)
Journal Article
Smith, J., & Vavak, F. (1999). Replacement strategies in steady state genetic algorithms: Dynamic environments. Journal of Computing and Information Technology, 7(1), 49-60
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/1099661Evolutionary 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.
Microprocessor design verification by two-phase evolution of variable length tests (1997)
Presentation / Conference
Smith, J., Bartley, M., & Fogarty, T. (1997, June). Microprocessor design verification by two-phase evolution of variable length tests. Paper presented at Proceedings of the 1997 IEEE Conference on Evolutionary Computation, IEEE Press, Piscataway, NJ, USA
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/s005000050009Genetic 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.
Self adaptation of mutation rates in a steady state genetic algorithm (1996)
Presentation / Conference
Smith, J., & Fogarty, T. (1996, June). Self adaptation of mutation rates in a steady state genetic algorithm. Paper presented at Proceedings of the 1996 IEEE Conference on Evolutionary Computation, IEEE Press, Piscataway, NJ, USA
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
Evolving software test data: GA's learn self expression (1996)
Book Chapter
Smith, J., & Fogarty, T. (1996). Evolving software test data: GA's learn self expression. In T. Fogarty (Ed.), Evolutionary Computing (137-146). Springer
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, GermanyLong 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.
Making early predictions of the accuracy of machine learning applications
Working Paper
Smith, J., Caleb-Solly, P., Tahir, M. A., Sannen, D., & van-Brussel, H. (2012). Making early predictions of the accuracy of machine learning applications
Teaching artificial intelligence with pac-man
Working Paper
Smith, J. (2009). Teaching artificial intelligence with pac-man
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
Stop wasting time: On predicting the success or failure of learning for industrial applications
Presentation / Conference
Smith, J., & Tahir, M. Stop wasting time: On predicting the success or failure of learning for industrial applications. Paper presented at Proceedings of the 8th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL'08), Springer, Berlin, Heidelberg, New York
Incorporation of adaptive mutation based on subjective evaluation in an interactive evolution strategy
Presentation / Conference
Caleb-Solly, P., & Smith, J. Incorporation of adaptive mutation based on subjective evaluation in an interactive evolution strategy. Paper presented at Proceedings of the IEEE Congress on Evolutionary Computation, Piscataway, NJ
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
Interactive evolutionary strategy based discovery of image segmentation parameters
Presentation / Conference
Caleb-Solly, P., & Smith, J. Interactive evolutionary strategy based discovery of image segmentation parameters. Paper presented at Adaptive Computing in Design and Manufacture VI, Springer, Berlin, Heidelberg, New York
Study of fitness landscapes for the HP model of protein structure prediction
Presentation / Conference
Duarte-Flores, S., & Smith, J. Study of fitness landscapes for the HP model of protein structure prediction. Paper presented at 2003 Congress on Evolutionary Computation (CEC'2003), Piscataway, NJ