EVOLUTION ENGINES AND ARTIFICIAL INTELLIGENCE
| Autor: | K. H. Becks, Andreas Hemker |
|---|---|
| Rok vydání: | 1994 |
| Předmět: |
education.field_of_study
Artificial neural network Computer science business.industry Population Evolutionary algorithm Intelligent decision support system General Physics and Astronomy Statistical and Nonlinear Physics Computational intelligence Marketing and artificial intelligence computer.software_genre Expert system Computer Science Applications Computational Theory and Mathematics Artificial intelligence Inference engine education business computer Mathematical Physics |
| Zdroj: | International Journal of Modern Physics C. :15-36 |
| ISSN: | 1793-6586 0129-1831 |
| DOI: | 10.1142/s0129183194000039 |
| Popis: | In the last years artificial intelligence has achieved great successes, mainly in the field of expert systems and neural networks. Nevertheless the road to truly intelligent systems is still obscured. Artificial intelligence systems with a broad range of cognitive abilities are not within sight. The limited competence of such systems (brittleness) is identified as a consequence of the top-down design process. The evolution principle of nature on the other hand shows an alternative and elegant way to build intelligent systems. We propose to take an evolution engine as the driving force for the bottom-up development of knowledge bases and for the optimization of the problem-solving process. A novel data analysis system for the high energy physics experiment DELPHI at CERN shows the practical relevance of this idea. The system is able to reconstruct the physical processes after the collision of particles by making use of the underlying standard model of elementary particle physics. The evolution engine acts as a global controller of a population of inference engines working on the reconstruction task. By implementing the system on the Connection Machine (Model CM-2) we use the full advantage of the inherent parallelization potential of the evolutionary approach. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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