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Prof Emma Hart's Outputs (188)

Artificial immune systems: proceedings of the 2nd international conference. (2003)
Presentation / Conference Contribution
(2003, September). Artificial immune systems: proceedings of the 2nd international conference. Presented at Second International Conference on Artificial Immune Systems, ICARIS 2003

This book constitutes the refereed proceedings of the Second International Conference on Artificial Immune Systems, ICARIS 2003, held in Edinburgh, UK in September 2003

Genetic algorithms and timetabling (2003)
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-funded project on this last year, and distribute a free package that handle... Read More about Genetic algorithms and timetabling.

A role for immunology in 'next generation' robots. (2003)
Presentation / Conference Contribution
Hart, E., Ross, P., Webb, A., & Lawson, A. (2003, September). A role for immunology in 'next generation' robots. Presented at Second International Conference, ICARIS 2003, Edinburgh, UK, September 1-3, 2003, Proceedings: volume 2787 of Lecture Notes on Computer Science: Artificial Immune Systems, Editors: Timmis, J., Bentley, P. and Hart, E., Springer, ISBN: 978-3-540-40766-9

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 is experimentally investigated. A more interesting research question is ho... Read More about A role for immunology in 'next generation' robots..

Requirements for getting a robot to grow up. (2003)
Presentation / Conference Contribution
Ross, P., Hart, E., Lawson, A., Webb, A., Prem, E., Poelz, P., & Morgavi, G. (2003, September). Requirements for getting a robot to grow up. Presented at 7th European Conference on Artificial Life, ECAL 2003: Advances in Artificial Life

Controlling a simulated Khepera with an XCS classifier system with memory. (2003)
Presentation / Conference Contribution
Webb, A., Hart, E., Ross, P., & Lawson, A. (2003, September). Controlling a simulated Khepera with an XCS classifier system with memory. Presented at 7th European Conference on Artificial Life, ECAL 2003: Advances in Artificial Life

Autonomous agents commonly suffer from perceptual aliasing in which differing situations are perceived as identical by the robots sensors, yet require different courses of action. One technique for addressing this problem is to use additional interna... Read More about Controlling a simulated Khepera with an XCS classifier system with memory..

Learning a procedure that can solve hard bin-packing problems: a new GA-based approach to hyperheuristics. (2003)
Presentation / Conference Contribution
Ross, P., Marin-Blazquez, J. G., Schulenburg, S., & Hart, E. (2003, July). Learning a procedure that can solve hard bin-packing problems: a new GA-based approach to hyperheuristics. Presented at Genetic and Evolutionary Computation Conference (GECCO) 2003

The idea underlying hyper-heuristics is to discover some
combination of familiar, straightforward heuristics that performs very well across a whole range of problems. To be worthwhile, such a combination should outperform all of the constituent heur... Read More about Learning a procedure that can solve hard bin-packing problems: a new GA-based approach to hyperheuristics..

A systematic investigation of GA performance on jobshop scheduling problems. (2003)
Presentation / Conference Contribution
Hart, E., & Ross, P. (2000, April). A systematic investigation of GA performance on jobshop scheduling problems. Presented at EvoWorkshops 2000: EvoIASP, EvoSCONDI, EvoTel, EvoSTIM, EvoRob, and EvoFlight, Edinburgh

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 gross over-generalisations, i.e that the observed performance of a GA on a sma... Read More about A systematic investigation of GA performance on jobshop scheduling problems..

Exploiting the analogy between immunology and sparse distributed memory. (2002)
Presentation / Conference Contribution
Hart, E., & Ross, P. (2002, September). Exploiting the analogy between immunology and sparse distributed memory. Presented at ICARIS 2002

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 clustering non-stationary data based on a combination of salient features... Read More about Exploiting the analogy between immunology and sparse distributed memory..

Combining choices of heuristics. (2002)
Book Chapter
Ross, P., & Hart, E. (2002). Combining choices of heuristics. In R. Sarker, M. Mohammadian, & X. Yao (Eds.), Evolutionary Optimization (229-252). Kluwer

Hyper-heuristics: learning to combine simple heuristics in bin-packing problems. (2002)
Presentation / Conference Contribution
Ross, P., Schulenburg, S., Marin-Blazquez, J. G., & Hart, E. (2002, July). Hyper-heuristics: learning to combine simple heuristics in bin-packing problems. Presented at Genetic and Evolutionary Computation Conference (GECCO)

Evolutionary algorithms (EAs) often appear to be a ‘black box’, neither offering worst-case bounds nor any guarantee of optimality when used to solve individual problems. They can also take much longer than non-evolutionary methods. We
try to addres... Read More about Hyper-heuristics: learning to combine simple heuristics in bin-packing problems..

Improving street based routing using building block mutations. (2002)
Presentation / Conference Contribution
Urquhart, N. B., Ross, P., Paechter, B., & Chisholm, K. (2002, April). Improving street based routing using building block mutations. Presented at Workshops on Applications of Evolutionary Computation EvoWorkshops 2002, Kinsale, Ireland

Street based routing (SBR) is a real-world inspired routing problem that builds routes within an urban area for mail deliveries. The authors have previously attempted to solve this problem using an Evolutionary Algorithm (EA). In this paper the autho... Read More about Improving street based routing using building block mutations..

GAVEL - a new tool for genetic algorithm visualization (2001)
Journal Article
Hart, E., & Ross, P. (2001). GAVEL - a new tool for genetic algorithm visualization. IEEE Transactions on Evolutionary Computation, 5(4), 335-348. https://doi.org/10.1109/4235.942528

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 genetic algorithm (GA) how crossover and mutation operations assembled the final result, where... Read More about GAVEL - a new tool for genetic algorithm visualization.

Clustering Moving Data with a Modified Immune Algorithm (2001)
Presentation / Conference Contribution
Hart, E., & Ross, P. (2001, April). Clustering Moving Data with a Modified Immune Algorithm. Presented at Workshops on Applications of Evolutionary Computation EvoWorkshops 2001, Como, Italy

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 have been proposed, none appear to specifically address the task of clustering... Read More about Clustering Moving Data with a Modified Immune Algorithm.

Street-based routing using an evolutionary algorithm (2001)
Presentation / Conference Contribution
Urquhart, N. B., Paechter, B., & Chisholm, K. (2001, April). Street-based routing using an evolutionary algorithm. Presented at Workshops on Applications of Evolutionary Computation EvoWorkshops 2001, Como, Italy

Much research has been carried out into solving routing problems using both Evolutionary Techniques and other methods. In this paper the authors investigate the usage of an Evolutionary Algorithms to solve the Street-Based Routing Problem (SBRP). The... Read More about Street-based routing using an evolutionary algorithm.

Real-world applications of evolutionary computing (2000)
Presentation / Conference Contribution
Cagnoni, S., Poli, R., Smith, G. D., Corne, D., Oates, M., Hart, E., Lanzi, P. L., Willem, E. J., Li, Y., Paechter, B., & Fogarty, T. C. (2000, April). Real-world applications of evolutionary computing. Presented at EvoWorkshops 2000, Edinburgh, Scotland

This book constitutes the refereed proceedings of six workshops on evolutionary computation held concurrently as EvoWorkshops 2000 in Edinburgh, Scotland, UK, in April 2000.
The 37 revised papers presented were carefully reviewed and selected by the... Read More about Real-world applications of evolutionary computing.

Enhancing the performance of a GA through visualisation. (2000)
Presentation / Conference Contribution
Hart, E., & Ross, P. (2000, July). Enhancing the performance of a GA through visualisation. Presented at GECCO 2000

This article describes a new tool for visualising genetic algorithms, (GAs) which is designed in order to allow the implicit mechanisms
of the GA | i.e. crossover and mutation | to be thoroughly analysed. This allows the user to determine whether th... Read More about Enhancing the performance of a GA through visualisation..

Optimising an evolutionary algorithm for scheduling (2000)
Presentation / Conference Contribution
Urquhart, N. B., Chisholm, K., & Paechter, B. (2000, April). Optimising an evolutionary algorithm for scheduling. Presented at EvoWorkshops 2000: EvoIASP, EvoSCONDI, EvoTel, EvoSTIM, EvoRob, and EvoFlight,, Edinburgh

This paper examines two techniques for setting the parameters of an evolutionary Algorithm (EA). The example EA used for test purposes undertakes a simple scheduling problem. An initial version of the EA was tested utilising a set of parameters that... Read More about Optimising an evolutionary algorithm for scheduling.