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This paper presents a highly parallel genetic algorithm, designed for concept induction in propositional and first order logics. The parallel architecture is an adaptation for set covering problems, of the diffusion model developed for optimization. The algorithm exhibits other two important methodological novelties related to Evolutionary Computation. First, it combines niches and species...
Inducing concept descriptions from examples requires a large space of hypotheses to be explored. Genetic algorithms offer an appealing alternative to traditional search algorithms, because of their multi-point search strategy. In this paper, the new system REGAL is described: it uses genetic algorithms to learn first order logic concept descriptions. Moreover, it can be easily integrated with a deductive...
Abstract. We report a case of gastric lipoma which manifested with an episode of acute gastrointestinal hemorrhage. Preoperative diagnosis was based on the US, CT, and MRI findings, as the results of gastrointestinal endoscopy were inconclusive. The role of current imaging methods, and particularly of MRI, is discussed.
Genetic Algorithms have been proposed by many authors for Machine Learning tasks. In fact, they are appealing for several different reasons, such as the flexibility, the great exploration power, and the possibility of exploiting parallel processing. Nevertheless, it is still controversial whether the genetic approach can really provide effective solutions to learning tasks, in comparison to other...
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