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Outputs (36)

Random feedbacks for selfish nodes detection in mobile ad hoc networks (2005)
Conference Proceeding
Djenouri, D., Ouali, N., Mahmoudi, A., & Badache, N. (2005). Random feedbacks for selfish nodes detection in mobile ad hoc networks. https://doi.org/10.1007/11567486_8

A mobile ad hoc network (MANET) is a temporary infrastructureless network, formed by a set of mobile hosts that dynamically establish their own network on the fly without relying on any central administration. Mobile hosts used in MANET have to ensur... Read More about Random feedbacks for selfish nodes detection in mobile ad hoc networks.

Coevolutionary species adaptation genetic algorithms: A continuing SAGA on coupled fitness landscapes (2005)
Journal Article
Bull, L. (2005). Coevolutionary species adaptation genetic algorithms: A continuing SAGA on coupled fitness landscapes. Lecture Notes in Artificial Intelligence, 3630 LNAI, 322-331. https://doi.org/10.1007/11553090_33

The Species Adaptation Genetic Algorithm (SAGA) was introduced to facilitate the open-ended evolution of artificial systems. The approach enables genotypes to increase in length through appropriate mutation operators and has been successfully exploit... Read More about Coevolutionary species adaptation genetic algorithms: A continuing SAGA on coupled fitness landscapes.

A tutorial for competent memetic algorithms: Model, taxonomy and design issues (2005)
Journal Article
Krasnogor, N., & Smith, J. (2005). A tutorial for competent memetic algorithms: Model, taxonomy and design issues. IEEE Transactions on Evolutionary Computation, 9(5), 474-488. https://doi.org/10.1109/TEVC.2005.850260

The combination of evolutionary algorithms with local search was named "memetic algorithms" (MAs) (Moscato, 1989). These methods are inspired by models of natural systems that combine the evolutionary adaptation of a population with individual learni... Read More about A tutorial for competent memetic algorithms: Model, taxonomy and design issues.

A tutorial for competent memetic algorithms: Model, taxonomy, and design issues (2005)
Journal Article
Krasnogor, N., & Smith, J. (2005). A tutorial for competent memetic algorithms: Model, taxonomy, and design issues. IEEE Transactions on Evolutionary Computation, 9(5), 474-488. https://doi.org/10.1109/TEVC.2005.850260

The combination of evolutionary algorithms with local search was named "memetic algorithms" (MAs) (Moscato, 1989). These methods are inspired by models of natural systems that combine the evolutionary adaptation of a population with individual learni... Read More about A tutorial for competent memetic algorithms: Model, taxonomy, and design issues.

A framework for classifying and evaluating process architecture methods (2005)
Journal Article
Green, S., & Ould, M. (2005). A framework for classifying and evaluating process architecture methods. Software Process: Improvement and Practice, 10(4), 415-425. https://doi.org/10.1002/spip.244

Piecemeal identification, development, and support of an organisation's processes may lead to problems: first, it may be difficult to identify which processes should be supported, and, second, it is unlikely that processes developed piecemeal will ei... Read More about A framework for classifying and evaluating process architecture methods.

Coevolutionary species adaptation genetic algorithms: growth and mutation on coupled fitness landscapes (2005)
Presentation / Conference
Bull, L. (2005, September). Coevolutionary species adaptation genetic algorithms: growth and mutation on coupled fitness landscapes. Paper presented at 2005 IEEE Congress on Eolutionary Computation, Edinburgh, UK

The species adaptation genetic algorithm (SAGA) was introduced to facilitate the open-ended evolution of artificial systems. The approach enables genotypes to increase in length through appropriate mutation operators. Most recently, this has been und... Read More about Coevolutionary species adaptation genetic algorithms: growth and mutation on coupled fitness landscapes.

Towards predicting spatial complexity: a learning classifier system approach to the identification of cellular automata (2005)
Presentation / Conference
Bull, L., Lawson, I., Adamatzky, A., & de Lacy Costello, B. (2005, September). Towards predicting spatial complexity: a learning classifier system approach to the identification of cellular automata. Paper presented at IEEE Congress on Evolutionary Computation, 2005, Edinburgh, UK

This paper presents a novel approach to the programming of automata-based simulation and computation using a machine learning technique. The identification of lattice-based automata for real-world applications is cast as a data mining problem. Our ap... Read More about Towards predicting spatial complexity: a learning classifier system approach to the identification of cellular automata.

Genetic programming with a genetic algorithm for feature construction and selection (2005)
Journal Article
Smith, M. G., & Bull, L. (2005). Genetic programming with a genetic algorithm for feature construction and selection. Genetic Programming and Evolvable Machines, 6(3), 265-281. https://doi.org/10.1007/s10710-005-2988-7

The use of machine learning techniques to automatically analyse data for information is becoming increasingly widespread. In this paper we primarily examine the use of Genetic Programming and a Genetic Algorithm to pre-process data before it is class... Read More about Genetic programming with a genetic algorithm for feature construction and selection.