Automatic generation of alternative starting positions for simple traditional board games

U. Ahmed, K. Chatterjee, S. Gulwani, in:, AAAI Press, 2015, pp. 745–752.

Conference Paper | Published | English
Author
; ;
Department
Series Title
Proceedings of the National Conference on Artificial Intelligence
Abstract
Simple board games, like Tic-Tac-Toe and CONNECT-4, play an important role not only in the development of mathematical and logical skills, but also in the emotional and social development. In this paper, we address the problem of generating targeted starting positions for such games. This can facilitate new approaches for bringing novice players to mastery, and also leads to discovery of interesting game variants. We present an approach that generates starting states of varying hardness levels for player 1 in a two-player board game, given rules of the board game, the desired number of steps required for player 1 to win, and the expertise levels of the two players. Our approach leverages symbolic methods and iterative simulation to efficiently search the extremely large state space. We present experimental results that include discovery of states of varying hardness levels for several simple grid-based board games. The presence of such states for standard game variants like 4×4 Tic-Tac-Toe opens up new games to be played that have never been played as the default start state is heavily biased.
Publishing Year
Date Published
2015-01-01
Acknowledgement
A Technical Report of this paper is available at: https://repository.ist.ac.at/id/eprint/146.
Volume
2
Page
745 - 752
Conference
AAAI: Conference on Artificial Intelligence
Conference Location
Austin, TX, USA
Conference Date
2015-01-25 – 2015-01-30
IST-REx-ID

Cite this

Ahmed U, Chatterjee K, Gulwani S. Automatic generation of alternative starting positions for simple traditional board games. In: Vol 2. AAAI Press; 2015:745-752.
Ahmed, U., Chatterjee, K., & Gulwani, S. (2015). Automatic generation of alternative starting positions for simple traditional board games (Vol. 2, pp. 745–752). Presented at the AAAI: Conference on Artificial Intelligence, Austin, TX, USA: AAAI Press.
Ahmed, Umair, Krishnendu Chatterjee, and Sumit Gulwani. “Automatic Generation of Alternative Starting Positions for Simple Traditional Board Games,” 2:745–52. AAAI Press, 2015.
U. Ahmed, K. Chatterjee, and S. Gulwani, “Automatic generation of alternative starting positions for simple traditional board games,” presented at the AAAI: Conference on Artificial Intelligence, Austin, TX, USA, 2015, vol. 2, pp. 745–752.
Ahmed U, Chatterjee K, Gulwani S. 2015. Automatic generation of alternative starting positions for simple traditional board games. AAAI: Conference on Artificial Intelligence, Proceedings of the National Conference on Artificial Intelligence, vol. 2. 745–752.
Ahmed, Umair, et al. Automatic Generation of Alternative Starting Positions for Simple Traditional Board Games. Vol. 2, AAAI Press, 2015, pp. 745–52.

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