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| Title Details: | |
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Exercise 13: Minimax και Alpha-Beta Pruning Algorithms |
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| Authors: |
Sgarbas, Kyriakos |
| Description: | |
| Abstract: |
This exercise implements the minimax and alpha-beta pruning algorithms with Prolog to search game state spaces (for two-player, full-information, zero-sum games) that are too large to fit in memory as dynamic facts and/or require too much search time. The game Pawns is used as an example, with 10 Chess pieces on a 5x5 chessboard.
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| Linguistic Editors: |
Sarafidis, Michail |
| Technical Editors: |
Papadogonas, Ioannis |
| Type: |
Chapter |
| Creation Date: | 02-05-2024 |
| Item Details: | |
| License: |
Attribution - NonCommercial - ShareAlike 4.0 International (CC BY-NC-SA 4.0) |
| Handle | http://hdl.handle.net/11419/13284 |
| Bibliographic Reference: | Sgarbas, K. (2024). Exercise 13: Minimax και Alpha-Beta Pruning Algorithms [Chapter]. In Sgarbas, K. 2024. Artificial Intelligence Laboratory Exercises with the Prolog Language [Laboratory Guide]. Kallipos, Open Academic Editions. https://hdl.handle.net/11419/13284 |
| Language: |
Greek |
| Is Part of: |
Artificial Intelligence Laboratory Exercises with the Prolog Language |
| Publication Origin: |
Kallipos, Open Academic Editions |