Advanced Artificial Intelligence

Lecturer:

Tutor:

Supervisor:

Department of Cybernetics

Synopsis:

The aim of the course is to provide an overview of advanced methods used at

development of intelligent systems. The following topics are discussed:

advanced methods of state space search, machine learning, data mining,

nature inspired algorithms (PSO, ACO, evolutionary algorithms, artificial

life), multiagent systems, and their applications.

Requirements:

Syllabus of lectures:

1. Nature of data, information and knowledge. Introduction to advanced

methods of state space search.

2. Methods of state space search (island-driven search, hierarchical search,

limited-horizon search, alpha-beta search, game strategies)

3. Machine learning - overview of classical methods

4. Multiple classifiers, ILP, relational logic

5. Operators of generalization and specialization, generalization theory

6. PAC learning, reinforcement learning

7. Application of machine learning to classification, prediction and other

areas

8. Data mining - methods, visualization, applications, learning of

associative rules

9. Distributed methods in learning and optimization

10. PSO, ACO, cellular automata, artificial immune systems, artificial life

11. Agent - definition, types and properties, models of architecture (BDI,

3bA), social behaviour

12. Coordination, cooperation and communication in multiagent systems

13. Models of cooperation (negotiations, market and auction mechanisms)

14. Planning, alliances, coalition formation, examples of applications

Syllabus of tutorials:

1.-3. Advanced algorithms of state space search

4.-9. Machine learning - Weka, programming of designed algorithm,

experiments with real data, comparison of results acquired using various

algorithms

10.-11. Experiments with PSO, ACO

12.-14. Multiagent systems - JADE, work with existing systems, Aglobe

platform

Study Objective:

Study materials:

[1] Wooldridge M., Jennings N.: Intelligent Agents: Theory and Practice. The

Knowledge Engineering Review, 10 (1995), No.2, pp. 115-1526

[2] Dorigo, M., V. Maniezzo, and A. Colorni. „The Ant System: optimization by a Colony of Cooperating Agents.“ IEEE Trans. Syst. Man Cybern. B 26 (1996): 29-41

[3] Russell, S., Norvig, P.: Artificial Intelligence, A Modern Approach,

Prentice Hall Series in AI. New Jersey, Englewood Cliffs, 1995

Note:

Further information:

No time-table has been prepared for this course

The course is a part of the following study plans: