INTELLIGENT SYSTEMS - PROGRAM
The course presents methodologies and techniques to implement intelligent systems for processing information and knowledge, i.e., systems which behaves like the human brain by employing computational intelligence approaches. In particular, the following main approaches will be studied: neural networks, fuzzy systems, and evolutionary computing.
- Neural networks: Definitions. Neurons: structures, perceptrons, RBF. Neural topologies: feed-forward, feedback, SOM. Learning: supervised, unsupervised. Performance. Optimization. Classification and clustering. Associative memories. Prediction. Function approximation. Applications.
- Fuzzy logic and systems: Fuzzy sets. Membership functions. Fuzzy rules. Defuzzification. Fuzzy reasoning. Fuzzy systems. Rough sets. Performance. Applications.
- Evolutionary computing: Genomic representation. Fitness functions. Selection. Genetic algorithms. Genetic programming. Evolutionary programming. Evolutionary strategies. Differential evolution. Swarm intelligence. Artificial immune systems.
- Hybrid systems