Özet
In this paper, we present a player profiling system applicable for both human players and bots in video games. The Vindinium artificial intelligence (AI) contest is selected as the test-bed for analyzing the performance of our system. In this game, AI bots compete with each other in a systematically generated environment to achieve the highest score. Our profiling method is based on Hidden Markov Model (HMM) constructed by using consecutive actions of AI bots and improved with the initial training phase and our sliding window approach. The method is evaluated for three different performance criteria: recognition of bots, grouping bots that have similar game styles and tracking changes in the strategy of a single bot through the game. The results indicate that the method is promising with 90,04% binary classification success in average.
Orijinal dil | İngilizce |
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Ana bilgisayar yayını başlığı | ICAART 2016 - Proceedings of the 8th International Conference on Agents and Artificial Intelligence |
Editörler | Jaap van den Herik, Joaquim Filipe, Joaquim Filipe |
Yayınlayan | SciTePress |
Sayfalar | 362-369 |
Sayfa sayısı | 8 |
ISBN (Elektronik) | 9789897581724 |
DOI'lar | |
Yayın durumu | Yayınlandı - 2016 |
Etkinlik | 8th International Conference on Agents and Artificial Intelligence, ICAART 2016 - Rome, Italy Süre: 24 Şub 2016 → 26 Şub 2016 |
Yayın serisi
Adı | ICAART 2016 - Proceedings of the 8th International Conference on Agents and Artificial Intelligence |
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Hacim | 2 |
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???event.eventtypes.event.conference??? | 8th International Conference on Agents and Artificial Intelligence, ICAART 2016 |
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Ülke/Bölge | Italy |
Şehir | Rome |
Periyot | 24/02/16 → 26/02/16 |
Bibliyografik not
Publisher Copyright:Copyright © 2016 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved.