Artificial Intelligence for Children of the Galaxy Computer Game
Název práce v češtině: | Umělá inteligence pro počítačovou hru Children of the Galaxy |
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Název v anglickém jazyce: | Artificial Intelligence for Children of the Galaxy Computer Game |
Klíčová slova: | umělá inteligence, Monte-Carlo Tree Search, počítačová hra, Children of the Galaxy |
Klíčová slova anglicky: | artificial player, Monte-Carlo Tree Search, computer game, Children of the Galaxy |
Akademický rok vypsání: | 2017/2018 |
Typ práce: | diplomová práce |
Jazyk práce: | angličtina |
Ústav: | Katedra softwaru a výuky informatiky (32-KSVI) |
Vedoucí / školitel: | Mgr. Jakub Gemrot, Ph.D. |
Řešitel: | skrytý![]() |
Datum přihlášení: | 30.10.2017 |
Datum zadání: | 30.10.2017 |
Datum potvrzení stud. oddělením: | 22.11.2017 |
Datum a čas obhajoby: | 10.09.2018 00:00 |
Datum odevzdání elektronické podoby: | 09.05.2018 |
Datum odevzdání tištěné podoby: | 10.05.2018 |
Datum proběhlé obhajoby: | 10.09.2018 |
Oponenti: | RNDr. Ing. Otakar Trunda, Ph.D. |
Zásady pro vypracování |
The aim of this work is to design an artificial intelligence (AI) for Children of the Galaxy (CotG), which is a 4X computer game. The student will first analyze the game from the artificial intelligence perspective and create a theoretical architecture for building a CotG AI solution. The student will then select one of its part for the implementation, e.g., a space battle micro-management. |
Seznam odborné literatury |
Churchill, D., & Buro, M. (2013, August). Portfolio greedy search and simulation for large-scale combat in StarCraft. In Computational Intelligence in Games (CIG), 2013 IEEE Conference on (pp. 1-8). IEEE.
Churchill, D., Saffidine, A., & Buro, M. (2012, October). Fast Heuristic Search for RTS Game Combat Scenarios. In AIIDE (pp. 112-117). Ontanón, S. (2013, November). The combinatorial multi-armed bandit problem and its application to real-time strategy games. In Ninth Artificial Intelligence and Interactive Digital Entertainment Conference. Justesen, N., Tillman, B., Togelius, J., & Risi, S. (2014, August). Script-and cluster-based UCT for StarCraft. In Computational Intelligence and Games (CIG), 2014 IEEE Conference on (pp. 1-8). IEEE. Gosling, T., Andruszkiewicz, P. (2014). Divide and Conquer, The Campaign AI of Total War: ROME II. Game/AI Conference Vienna [online]. 2014. [Accessed 21 November 2016]. Available from: http://archives.nucl.ai/recording/divide-and-conquer-the-campaign-ai-of-total-war-rome-ii/ Andruszkiewicz, P. (2015). Optimizing MCTS Performance for Tactical Coordination in TOTAL WAR: ATILLA. nucl.ai Conference [online]. 2015. [Accessed 21 November 2016]. Available from: https://archives.nucl.ai/recording/optimizing-mcts-performance-for-tactical-coordination-in-total-war-atilla/ Browne, C. B., Powley, E., Whitehouse, D., Lucas, S. M., Cowling, P. I., Rohlfshagen, P., ... & Colton, S. (2012). A survey of monte carlo tree search methods. IEEE Transactions on Computational Intelligence and AI in games, 4(1), 1-43. |