SUBJECT

Artificial intelligence

lecture

bachelor

Faculty of Informatics

3

Semester 6

Spring semester

• Problem modeling and graph representation. State-space representation. Solving problems by irrevocable searches: hill-climbing search, tabu search, algorithm of simulated annealing, genetic algorithms.

• Tentative searches: backtracking, heuristic graph-search methods.

• Decomposition and AND/OR graphs. Two-player games.

• Logical reasoning by resolution and rule based systems.

• Reasoning by uncertain knowledge. Probabilistic reasoning systems. Semantic nets and frames.

• Decision trees, machine learning general logical formulas, artificial neural networks.

• N. J. Nilsson: Principles of Artificial Intelligence (Springer-Verlag, 1982)

• E. Rich, K. Knigth: Artificial Intelligence (MacGraw-Hill Book Company, 1991)

• N. J. Nilsson: Artificial Intelligence: a new synthesis (Morgan Kaufmann Pub. 1998)

• Fekete I., Gregorics T., Nagy S.: Bevezetés a Mesterséges Intelligenciába (LSI, 1990, 1999)

• Futó I. (szerk.): Mesterséges intelligencia (Aula Kiadó, 1999)

• Russel, J. S., Norvig, P.: MI - modern megközelítésben (Panem Kft, 2000)

• Gregorics Tibor: Mesterséges intelligencia (ELTE IK Digitális Könyvtár 2008)

Recommended literature:

• M.R. Genesereth, N.J. Nilsson: Logical Foundations of Artificial Intelligent (Morgan Kaufmann Pub. 1987)
• Mérő L.: Észjárások (TypoTEX, 1994)