Planning and game playing
Semestr: Summer
Range: 2P+2C
Completion:
Credits: 6
Programme type: Master
Study form: Fulltime
Course language:
Summary:
This course provides an introduction to classical AI planning (linear, nonliner planning, graph-plan planning, heuristic planning, SAT-based planning) and game-tree representation and methods of adversarial search (such as minimax and alpha/beta pruning).
Keywords:
Course syllabus:
1. planning problem representation and planning problem komplexity
2. linear planning, TOPLAN algorithm,
3. nonlineární planning, causal links thread resolution
4. Graf-oriented planning
5. planning by means of SAT
6. Introduction to game playing
7. Minimax, alfa-beta prunning
8. Advenced methods of adversarial planning
9. Hierarchical HTN planning
10. Heuristic planning
11. Contingency planning, temporal planning
12. Planning a probability
13. Planning in game playing
Seminar syllabus:
1. Planning problems
2. Semestral project specification: design and development of a general planner
3. - 5. Laboratories
6. Game playing algorithms
7. Semestral project specification: design and development of a game playing algorithm
8. - 12. Laboratories
13. Competition
Literature:
Nau, D., Ghallab, M., and Traverso, P. 2004 Automated Planning: Theory
and Practice. Morgan Kaufmann Publishers Inc.
Russell, S. J. and Norvig, P. 2003 Artificial Intelligence: a Modern
Approach. 2. Pearson Education.