This paper proposes a new approach for constructing fuzzy knowledge bases using evolutionary meth... more This paper proposes a new approach for constructing fuzzy knowledge bases using evolutionary methods. We have designed a genetic algorithm that automatically builds neuro-fuzzy architectures based on a new indirect encoding method. The neuro-fuzzy architecture represents the fuzzy knowledge base that solves a given problem; the search for this architecture takes advantage of a local search procedure that improves the chromosomes at each generation. Experiments conducted both on artificially generated and real world problems confirm the effectiveness of the proposed approach.
We propose a new technique for building neural networks which takes inspiration from the biology ... more We propose a new technique for building neural networks which takes inspiration from the biology of neural cells. In our model neurons are fixed in space, and their connections are grown according to a given rule, for building any type of network without training. The growing rule is encoded in each cell's genetic code, and the strength of the connections depends on their length. Rules are generated using an evolutionary process. This process mimics the brains innate capabilities codifying this complex biological ...
This paper proposes a new approach for constructing fuzzy knowledge bases using evolutionary meth... more This paper proposes a new approach for constructing fuzzy knowledge bases using evolutionary methods. We have designed a genetic algorithm that automatically builds neuro-fuzzy architectures based on a new indirect encoding method. The neuro-fuzzy architecture represents the fuzzy knowledge base that solves a given problem; the search for this architecture takes advantage of a local search procedure that improves the chromosomes at each generation. Experiments conducted both on artificially generated and real world problems confirm the effectiveness of the proposed approach.
We propose a new technique for building neural networks which takes inspiration from the biology ... more We propose a new technique for building neural networks which takes inspiration from the biology of neural cells. In our model neurons are fixed in space, and their connections are grown according to a given rule, for building any type of network without training. The growing rule is encoded in each cell's genetic code, and the strength of the connections depends on their length. Rules are generated using an evolutionary process. This process mimics the brains innate capabilities codifying this complex biological ...
Uploads
Papers by A. Carrascal