Hyper Heuristics: an emerging direction in modern search technology.
Book Chapter
Burke, E., Hart, E., Kendall, G., Newall, J., Ross, P., & Schulenburg, S. (2003)
Hyper Heuristics: an emerging direction in modern search technology. In F. Glover, & G. A. Kochenberger (Eds.), Handbook of MetaHeuristics, 457-474. Springer US. https://doi.org/10.1007/0-306-48056-5_16
Requirements for getting a robot to grow-up
Conference Proceeding
Ross, P., Hart, E., Lawson, A., Webb, A., Prem, E., Poelz, P., & Morgavi, G. (2003)
Requirements for getting a robot to grow-up. In W. Banzhaf, T. Christaller, P. Dittrich, J. T. Kim, & J. Ziegler (Eds.), Advances in Artificial Life 7th European Conference, ECAL 2003, Dortmund, Germany, September 14-17, 2003. Proceedings. , (847-856). https://doi.org/10.1007/978-3-540-39432-7_91
Much of current robot research is about learning tasks in which the task to be achieved is pre-specified, a suitable technology for the task is chosen and the learning process...
Genetic algorithms and timetabling
Book Chapter
Ross, P., Hart, E., & Corne, D. (2003)
Genetic algorithms and timetabling. In A. Ghosh, & K. Tsutsui (Eds.), Advances in Evolutionary Optimisation. Springer. https://doi.org/10.1007/978-3-642-18965-4_30
Genetic algorithms can be used to search very large spaces, and it would seem natural to use them for tackling the nastier kinds of timetabling problem. We completed an EPSRC-...
A systematic investigation of GA performance on jobshop scheduling problems.
Conference Proceeding
Hart, E., & Ross, P. (2003)
A systematic investigation of GA performance on jobshop scheduling problems. In Real-World Applications of Evolutionary Computing. , (280-289). https://doi.org/10.1007/3-540-45561-2_27
Although there has been a wealth of work reported in the literature on the application of genetic algorithms (GAs) to jobshop scheduling problems, much of it contains some gro...
Routing using evolutionary agents and proactive transitions.
Book
Urquhart, N. B., Ross, P., Paechter, B., & Chisholm, K. (2002)
Routing using evolutionary agents and proactive transitions. In Applications of Evolutionary Computing, 696-705. Springer-Verlag
The authors have previously introduced the concept of building a delivery network using an agent-based system. The delivery networks are built in response to a real-world prob...
Solving a real world routing problem using multiple evolutionary algorithms.
Conference Proceeding
Urquhart, N. B., Ross, P., Paechter, B., & Chisholm, K. (2002)
Solving a real world routing problem using multiple evolutionary algorithms. In Parallel Problem Solving from Nature — PPSN VII. , (871-880). https://doi.org/10.1007/3-540-45712-7_84
This paper investigates the solving of a real world routing problem using evolutionary algorithms embedded within a Multi-agent system (MAS). An architecture for the MAS is pr...
Exploiting the analogy between immunology and sparse distributed memory.
Conference Proceeding
Hart, E., & Ross, P. (2001)
Exploiting the analogy between immunology and sparse distributed memory. In J. Timmis, & P. J. Bentley (Eds.), ICARIS 2002 : 1st International Conference on Artificial Immune Systems, 59-67
The relationship between immunological memory and a class of associative memories known as sparse distributed memories (SDM) is well known. This paper proposes a new model for...
Combining choices of heuristics.
Book
Ross, P., & Hart, E. (2001)
Combining choices of heuristics. In R. Sarker, M. Mohammadian, & X. Yao (Eds.), Evolutionary Optimization, 229-252. Kluwer
GAVEL - a new tool for genetic algorithm visualization
Journal Article
Ross, P., Hart, E., & Ross, P. (2000)
GAVEL - a new tool for genetic algorithm visualization. IEEE Transactions on Evolutionary Computation, 5(4), 335-348. doi:10.1109/4235.942528
Abstract—This paper surveys the state of the art in evolutionary algorithm visualization and describes a new tool called GAVEL. It provides a means to examine in a generationa...
Clustering Moving Data with a Modified Immune Algorithm
Conference Proceeding
Hart, E., & Ross, P. (2001)
Clustering Moving Data with a Modified Immune Algorithm. In E. Boers (Ed.), Applications of Evolutionary Computing, 394-403. https://doi.org/10.1007/3-540-45365-2_41
In this paper we present a prototype of a new model for performing clustering in large, non-static databases. Although many machine learning algorithms for data clustering hav...