Artificial Intelligence for Biomedical Engineering
- Department of Biomedical Informatics
Definition of artificial intelligence. State and state space, searching within state space - informed methods (gradient-based alg., branch and bound, A*) and non-informed methods (depth-first and breadth-first search methods). Mathematical logic, resolution. Recognition - feature and structural-based methods, classification, criterion of minimal distance and minimal error. Machine learning, decision trees. Knowledge-based and expert systems.
Exam: Written and oral.
- Syllabus of lectures:
1. Definition of artificial intelligence, systems and models, feedback, adaptation.
2. State and state space, searching state space.
3. Informed methods of searching (branch and bound, A*) and non-informed methods of searching (deep-first and wide-first search).
4. Mathematical logic (propositional and predicate calculus), proving of theorems, resoltion.
5. Recognition - feature-based methods, classification, criterion of minimal distance and minimal error.
6. Recognition - structural methods, deformation schema, classification
7. Analysis, synthesis and processing of speech. Cepstral analysis, dynamic programming, syntax and semantics.
8. Machine learning, decision trees.
9. Knowledge and expert systems (diagnistic, planning and hybrid). Extraction of knowledge for expert systems.
10. Distributed artificial intelligence, multi-agent systems (reactive, intencional, social agents), coordination, cooperation, communication.
11. Evolution techniques, genetic algorithms, evolution programming, genetic programming, gramatic evolution.
12. Neural networks, classifiers, approximators, multilayer perceptron network, methods of learning and recalling.
13. Fuzzy logic and fuzzy systems.
14. Artificial intelligence in control engineering and robotics.
- Syllabus of tutorials:
There are no training lessons.
- Study Objective:
To introduce students to basics of artificial intelligence and different methods that are used in the area of artificial intelligence.
- Study materials:
Philip C. Jackson: Introduction to Artificial Intelligence, 1985, ISBN: 048624864X
Henry Brighton, Howard Selina: Introducing Artificial Intelligence, 2004, ISBN: 1840464631
- Further information:
- No time-table has been prepared for this course
- The course is a part of the following study plans: