Searching for authors named "Caroline Ravise" – sorted by Relevance.
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A Genetic Algorithm Led by Induction
- . Genetic algorithms are widely applicable, but are slower than other optimisation methods. Operators disruptiveness is one reason of this slowness. To solve this problem, one can control genetic operators by inductive learning. Crossovers control was first examined because of their good position am
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Toward Civilized Evolution: Developing Inhibitions
- Most evolutionary algorithms concerned with a memory of evolution aim at memorizing and reusing the recipes of past successes (e.g. fruitful operators or fruitful mutation directions) . The scheme proposed here follows the opposite track, and memorizes the past failures of evolution (unfit offspring
- Cited by 13 (1 self) – Add To MetaCart
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Inductive Learning of Mutation Step-size in Evolutionary Parameter Optimization
- . The problem of setting the mutation step-size for real-coded evolutionary algorithms has received different answers: exogenous rules like the 1=5 rule, or endogenous factor like the self-adaptation of the stepsize in the Gaussian mutation of modern Evolution Strategies. On the other hand, in the b
- Cited by 4 (0 self) – Add To MetaCart
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Controlling Evolution by means of Machine Learning
- A safe control of evolution consists in preventing past errors of evolution to be repeated, which could be done by keeping track of the history of evolution. But maintaining and exploiting the complete history is intractable. This paper therefore investigates the use of machine learning (ML), in ord
- Cited by 3 (1 self) – Add To MetaCart

