Title Details: | |
Exercise 12: Adversarial Search |
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Authors: |
Sgarbas, Kyriakos |
Description: | |
Abstract: |
In this exercise, the two-player, full-information, zero-sum games NIM and Tic-Tac-Toe are used as examples to implement in Prolog full state-space search algorithms that are able to label positions as won, lost, or draw (tied), suggest next moves, and identify optimal strategies. Dynamic events are used so that the search process generates new knowledge during the execution of the programs.
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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/11419/13283 |
Bibliographic Reference: | Sgarbas, K. (2024). Exercise 12: Adversarial Search [Chapter]. In Sgarbas, K. 2024. Artificial Intelligence Laboratory Exercises with the Prolog Language [Laboratory Guide]. Kallipos, Open Academic Editions. https://hdl.handle.net/11419/13283 |
Language: |
Greek |
Is Part of: |
Artificial Intelligence Laboratory Exercises with the Prolog Language |
Publication Origin: |
Kallipos, Open Academic Editions |