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Motivated by the intention to increase the expressive power of learning classifier systems, we developed a new Xcs derivative, Fox-cs, where the classifier and observation languages are a subset of first order logic. We found that Fox-cs was viable at tasks in two relational task domains, poker and blocks world, which cannot be represented easily using(More)
There is mounting evidence that family functioning is linked to childhood overweight and obesity, and that both of these are associated with health-related behaviours and adverse health outcomes in children and adolescents. This paper systematically examines the peer-reviewed evidence regarding the relationship between child and adolescent overweight and(More)
BACKGROUND Several lines of evidence suggest that transcription factors are involved in the pathogenesis of Multiple Sclerosis (MS) but complete mapping of the whole network has been elusive. One of the reasons is that there are several clinical subtypes of MS and transcription factors that may be involved in one subtype may not be in others. We investigate(More)
Therapies consisting of a combination of agents are an attractive proposition, especially in the context of diseases such as cancer, which can manifest with a variety of tumor types in a single case. However uncovering usable drug combinations is expensive both financially and temporally. By employing computational methods to identify candidate combinations(More)
Policy transfer occurs when a system transfers a policy learnt for one task to another task with little or no retraining, and allows a system to perform robustly and learn efficiently, especially when the new task is more complex than the original task. In this paper we report on work in progress into policy transfer using a relational learning classifier(More)
Profiling of the learning classifier system XCS [11] has revealed that its execution time tends to be dominated by rule matching [8], it is therefore important for rule matching to be efficient. To date, the fastest speedups for matching have been achieved by exploiting parallelism [8], but efficient sequential approaches, such as bitset and "specificity"(More)