Subject description - AE4M36PAH

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AE4M36PAH Planning and game playing
Roles:  Extent of teaching:2P+2C
Department:13136 Language of teaching:EN
Guarantors:  Completion:Z,ZK
Lecturers:  Credits:6
Tutors:  Semester:L


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).

Course outlines:

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

Exercises outline:

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


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.



Subject is included into these academic programs:

Program Branch Role Recommended semester

Page updated 5.10.2022 15:51:18, semester: Z,L/2022-3, Z/2024-5, L/2021-2, Send comments about the content to the Administrators of the Academic Programs Proposal and Realization: I. Halaška (K336), J. Novák (K336)