A hyperheuristic methodology to generate adaptive strategies for games
Hyperheuristics have been successfully applied in solving a variety of computational search problems. In this study, we investigate a hyper-heuristic methodology to generate adaptive strategies for games. Based on a set of low-level heuristics (or strategies), a hyper-heuristic game player can gener...
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| Format: | Article |
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IEEE
2017
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| Online Access: | https://eprints.nottingham.ac.uk/49531/ |
| _version_ | 1848798017820295168 |
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| author | Li, Jiawei Kendall, G. |
| author_facet | Li, Jiawei Kendall, G. |
| author_sort | Li, Jiawei |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | Hyperheuristics have been successfully applied in solving a variety of computational search problems. In this study, we investigate a hyper-heuristic methodology to generate adaptive strategies for games. Based on a set of low-level heuristics (or strategies), a hyper-heuristic game player can generate strategies which adapt to both the behaviour of the co-players and the game dynamics. By using a simple heuristic selection mechanism, a number of existing heuristics for specialised games can be integrated into an automated game player. As examples, we develop hyperheuristic game players for three games: iterated prisoner's dilemma, repeated Goofspiel and the competitive traveling salesmen problem. The results demonstrate that a hyperheuristic game player outperforms the low-level heuristics, when used individually in game playing and it can generate adaptive strategies even if the low-level heuristics are deterministic. This methodology provides an efficient way to develop new strategies for games based on existing strategies. |
| first_indexed | 2025-11-14T20:13:05Z |
| format | Article |
| id | nottingham-49531 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T20:13:05Z |
| publishDate | 2017 |
| publisher | IEEE |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-495312020-05-04T19:58:24Z https://eprints.nottingham.ac.uk/49531/ A hyperheuristic methodology to generate adaptive strategies for games Li, Jiawei Kendall, G. Hyperheuristics have been successfully applied in solving a variety of computational search problems. In this study, we investigate a hyper-heuristic methodology to generate adaptive strategies for games. Based on a set of low-level heuristics (or strategies), a hyper-heuristic game player can generate strategies which adapt to both the behaviour of the co-players and the game dynamics. By using a simple heuristic selection mechanism, a number of existing heuristics for specialised games can be integrated into an automated game player. As examples, we develop hyperheuristic game players for three games: iterated prisoner's dilemma, repeated Goofspiel and the competitive traveling salesmen problem. The results demonstrate that a hyperheuristic game player outperforms the low-level heuristics, when used individually in game playing and it can generate adaptive strategies even if the low-level heuristics are deterministic. This methodology provides an efficient way to develop new strategies for games based on existing strategies. IEEE 2017-03 Article PeerReviewed Li, Jiawei and Kendall, G. (2017) A hyperheuristic methodology to generate adaptive strategies for games. IEEE Transactions on Computational Intelligence and AI in Games, 9 (1). pp. 1-10. ISSN 1943-0698 Competitive traveling salesmen problem; game; Goofspiel; hyperheuristic; iterated prisoner's dilemma (IPD) http://ieeexplore.ieee.org/document/7017583/ doi:10.1109/TCIAIG.2015.2394780 doi:10.1109/TCIAIG.2015.2394780 |
| spellingShingle | Competitive traveling salesmen problem; game; Goofspiel; hyperheuristic; iterated prisoner's dilemma (IPD) Li, Jiawei Kendall, G. A hyperheuristic methodology to generate adaptive strategies for games |
| title | A hyperheuristic methodology to generate adaptive strategies for games |
| title_full | A hyperheuristic methodology to generate adaptive strategies for games |
| title_fullStr | A hyperheuristic methodology to generate adaptive strategies for games |
| title_full_unstemmed | A hyperheuristic methodology to generate adaptive strategies for games |
| title_short | A hyperheuristic methodology to generate adaptive strategies for games |
| title_sort | hyperheuristic methodology to generate adaptive strategies for games |
| topic | Competitive traveling salesmen problem; game; Goofspiel; hyperheuristic; iterated prisoner's dilemma (IPD) |
| url | https://eprints.nottingham.ac.uk/49531/ https://eprints.nottingham.ac.uk/49531/ https://eprints.nottingham.ac.uk/49531/ |