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All Outputs (7)

Verbal and nonverbal elicitation techniques in the subjective assessment of spatial sound reproduction (2001)
Journal Article
Mason, R., Ford, N., Rumsey, F., & De Bruyn, B. (2001). Verbal and nonverbal elicitation techniques in the subjective assessment of spatial sound reproduction. Journal of the Audio Engineering Society, 49, 366--384

Current research into spatial audio has shown an increasing interest in the way subjective attributes of reproduced sound are elicited from listeners. The emphasis at present is on verbal semantics, however, studies suggest that nonverbal methods of... Read More about Verbal and nonverbal elicitation techniques in the subjective assessment of spatial sound reproduction.

Simple models of coevolutionary genetic algorithms (2001)
Journal Article
Bull, L. (2001). Simple models of coevolutionary genetic algorithms. Artificial Life and Robotics, 5(1), 58-66. https://doi.org/10.1007/BF02481321

The use of evolutionary computing techniques in coevolutionary/multiagent systems is becoming increasingly popular. This paper presents some simple models of the genetic algorithm in such systems, with the aim of examining the effects of different ty... Read More about Simple models of coevolutionary genetic algorithms.

Coevolving functions in genetic programming (2001)
Journal Article
Ahluwalia, M., & Bull, L. (2001). Coevolving functions in genetic programming. Journal of Systems Architecture, 47(7), 573-585. https://doi.org/10.1016/S1383-7621%2801%2900016-9

In this paper we introduce a new approach to the use of automatically defined functions (ADFs) within genetic programming. The technique consists of evolving a number of separate sub-populations of functions which can be used by a population of evolv... Read More about Coevolving functions in genetic programming.

Simple Markov models of the genetic algorithm in classifier systems: multi-step tasks (2001)
Journal Article
Bull, L. (2001). Simple Markov models of the genetic algorithm in classifier systems: multi-step tasks. Lecture Notes in Artificial Intelligence, 1996, 29-36

Abstract Michigan-style Classifier Systems use Genetic Algorithms to facilitate rule discovery. This paper presents a simple Markov model of the algorithm in such systems, with the aim of examining the effects of different types of interdependence be... Read More about Simple Markov models of the genetic algorithm in classifier systems: multi-step tasks.