Enhancing Artificial Intelligence on a Real Mobile Game
Mobile games represent a killer application that is attracting millions of subscribers worldwide. One of the aspects crucial to the commercial success of a game is ensuring an appropriately challenging artificial intelligence (AI) algorithm against which to play. However, creating this component is...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2009-01-01
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| Series: | International Journal of Computer Games Technology |
| Online Access: | http://dx.doi.org/10.1155/2009/456169 |
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| _version_ | 1832549357950337024 |
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| author | Fabio Aiolli Claudio E. Palazzi |
| author_facet | Fabio Aiolli Claudio E. Palazzi |
| author_sort | Fabio Aiolli |
| collection | DOAJ |
| description | Mobile games represent a killer application that is attracting millions of subscribers worldwide. One of the aspects crucial to the commercial success of a game is ensuring an appropriately challenging artificial intelligence (AI) algorithm against which to play. However, creating this component is particularly complex as classic search AI algorithms cannot be employed by limited devices such as mobile phones or, even on more powerful computers, when considering imperfect information games (i.e., games in which participants do not a complete knowledge of the game state at any moment). In this paper, we propose to solve this issue by resorting to a machine learning algorithm which uses profiling functionalities in order to infer the missing information, thus making the AI able to efficiently adapt its strategies to the human opponent. We studied a simple and computationally light machine learning method that can be employed with success,
enabling AI improvements for imperfect information games even on mobile phones. We created a mobile phone-based version of a game called Ghosts and present results which clearly show the ability of our algorithm to quickly improve its own predictive performance as far as the number of games against the same human opponent increases. |
| format | Article |
| id | doaj-art-173287fd623c4ab0a23bffd81a99016c |
| institution | Kabale University |
| issn | 1687-7047 1687-7055 |
| language | English |
| publishDate | 2009-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Computer Games Technology |
| spelling | doaj-art-173287fd623c4ab0a23bffd81a99016c2025-02-03T06:11:29ZengWileyInternational Journal of Computer Games Technology1687-70471687-70552009-01-01200910.1155/2009/456169456169Enhancing Artificial Intelligence on a Real Mobile GameFabio Aiolli0Claudio E. Palazzi1Department of Pure and Applied Mathematics, University of Padova, Via Trieste 63, 35131 Padova, ItalyDepartment of Pure and Applied Mathematics, University of Padova, Via Trieste 63, 35131 Padova, ItalyMobile games represent a killer application that is attracting millions of subscribers worldwide. One of the aspects crucial to the commercial success of a game is ensuring an appropriately challenging artificial intelligence (AI) algorithm against which to play. However, creating this component is particularly complex as classic search AI algorithms cannot be employed by limited devices such as mobile phones or, even on more powerful computers, when considering imperfect information games (i.e., games in which participants do not a complete knowledge of the game state at any moment). In this paper, we propose to solve this issue by resorting to a machine learning algorithm which uses profiling functionalities in order to infer the missing information, thus making the AI able to efficiently adapt its strategies to the human opponent. We studied a simple and computationally light machine learning method that can be employed with success, enabling AI improvements for imperfect information games even on mobile phones. We created a mobile phone-based version of a game called Ghosts and present results which clearly show the ability of our algorithm to quickly improve its own predictive performance as far as the number of games against the same human opponent increases.http://dx.doi.org/10.1155/2009/456169 |
| spellingShingle | Fabio Aiolli Claudio E. Palazzi Enhancing Artificial Intelligence on a Real Mobile Game International Journal of Computer Games Technology |
| title | Enhancing Artificial Intelligence on a Real Mobile Game |
| title_full | Enhancing Artificial Intelligence on a Real Mobile Game |
| title_fullStr | Enhancing Artificial Intelligence on a Real Mobile Game |
| title_full_unstemmed | Enhancing Artificial Intelligence on a Real Mobile Game |
| title_short | Enhancing Artificial Intelligence on a Real Mobile Game |
| title_sort | enhancing artificial intelligence on a real mobile game |
| url | http://dx.doi.org/10.1155/2009/456169 |
| work_keys_str_mv | AT fabioaiolli enhancingartificialintelligenceonarealmobilegame AT claudioepalazzi enhancingartificialintelligenceonarealmobilegame |