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This research
field shows us how to use simulated evolution to achieve relationship
between learning and intelligence. This relationship we can achieve by
modeling evolutionary processes and in that way we can create entities
capable of generating intelligent behavior. Systems needed in that problem
solving area based on principles of evolution. Such systems maintain a
population of potential solutions, they have some selection process based
on fitness of individuals, and some genetic operators. There are more
algorithms underlie evolutionary systems: Evolutionary Strategies, Evolutionary
Programming, Genetic Algorithms and Genetic Programming.
The main research
topics are:
1. EVOLUTIONARY FUZZY SYSTEMS
2. EVOLUTYONARY NEURAL SYSTEMS
3. GENETIC FUZZY NEURAL SYSTEMS
4. EVOLUTIONARY METHODS FOR MOBILE ROBOT MOTION CONTROL
5. GENETIC ALGORITHMS IN SPEECH RECOGNITION SYSTEMS
6. GENETIC ALGORITHMS IN COMPUTATIONALL INTELLIGENCE
7. GENETIC ALGORITHMS IN COMMUNICATION SYSTEMS
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