Sephton, Nicholas John, Cowling, Peter Ivan orcid.org/0000-0003-1310-6683, Devlin, Sam orcid.org/0000-0002-7769-3090 et al. (2 more authors) (2016) Using Association Rule Mining to Predict Opponent Deck Content in Android: Netrunner. In: IEEE Computational Intelligence and Games Conference (CIG 2016), 20-23 Sep 2016, Greece.
Abstract
As part of their design, card games often include information that is hidden from opponents and represents a strategic advantage if discovered. A player that can discover this information will be able to alter their strategy based on the nature of that information, and therefore become a more competent opponent. In this paper, we employ association rule-mining techniques for predicting item multisets, and show them to be effective in predicting the content of Netrunner decks. We then apply different modifications based on heuristic knowledge of the Netrunner game, and show the effectiveness of techniques which consider this knowledge during rule generation and prediction.
Metadata
Item Type: | Conference or Workshop Item |
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Authors/Creators: |
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Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Computer Science (York) |
Funding Information: | Funder Grant number EPSRC EP/K039857/1 EPSRC EP/M023265/1 |
Depositing User: | Pure (York) |
Date Deposited: | 16 Sep 2016 09:03 |
Last Modified: | 23 Jan 2025 00:42 |
Status: | Published |
Refereed: | Yes |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:104807 |