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Environments of strategic video games are complex and they can be characterized (not only) as non-deterministic,
simulated in real-time and having extremely large game trees. This course focuses on problems of using
traditional search algorithms in such environments. A script space will be presented as an alternative to an action
space, search algorithms suitable for durative actions are discussed and Monte-Carlo Tree Search family of
algorithms will be presented. The possibility of using artificial evolution for game tree pruning.
Last update: Holan Tomáš, RNDr., Ph.D. (09.05.2024)
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To gain overview about algorithms and techniques which can be used for the implementation of artificial intelligence for strategic videogames. Last update: Holan Tomáš, RNDr., Ph.D. (09.05.2024)
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The course ends with successfully completing an exam and gaining a credit from the labs.
The credit from the labs is not required for taking the exam.
To gain a credit from labs, an active participation on labs is required as well as an implementation of chosen algorithm presented during lectures. Last update: Holan Tomáš, RNDr., Ph.D. (09.05.2024)
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Books: RUSSEL, Stuart J. and NORVIG, Peter, 2010. Artificial Intelligence: A Modern Approach. 3rd. Upper Saddle River: Prentice Hall. ISBN 978-0-13-604259-4.
Scientific articles: AUER, Peter, CESA-BIANCHI, Nicolo and FISCHER, Paul, 2002. Finite-time Analysis of the Multiarmed Bandit Problem. Machine Learning. 2002. Vol. 47, p. 235-256. BRANAVAN, S. R. K.; SILVER, David; BARZILAY, Regina. Non-linear monte-carlo search in civilization ii. In: IJCAI. 2011. p. 2404-2410. BROWNE, Cameron B., et al. A survey of monte carlo tree search methods. IEEE Transactions on Computational Intelligence and AI in games, 2012, 4.1: 1-43. CHURCHILL, David; BURO, Michael. Portfolio greedy search and simulation for large-scale combat in StarCraft. In: Computational Intelligence in Games (CIG), 2013 IEEE Conference on. IEEE, 2013. p. 1-8. CHURCHILL, David; SAFFIDINE, Abdallah; BURO, Michael. Fast Heuristic Search for RTS Game Combat Scenarios. In: AIIDE. 2012. p. 112-117. FURTAK, Timothy; BURO, Michael. On the Complexity of Two-Player Attrition Games Played on Graphs. In: AIIDE. 2010. GOSLING, Tim and ANDRUSZKIEWICZ, Piotr, 2014. Divide and Conquer, The Campaign AI of Total War: ROME II. Game/AI Conference Vienna [online]. 2014. [Accessed 20 May 2016]. Available from: https://archives.nucl.ai/recording/divide-and-conquer-the-campaign-ai-of-total-war-rome-ii/ JUSTESEN, Niels, et al. Script-and cluster-based UCT for StarCraft. In: Computational Intelligence and Games (CIG), 2014 IEEE Conference on. IEEE, 2014. p. 1-8. ONTANÓN, Santiago. Informed monte carlo tree search for real-time strategy games. In: Computational Intelligence and Games (CIG), 2016 IEEE Conference on. IEEE, 2016. p. 1-8. ONTANÓN, Santiago. The combinatorial multi-armed bandit problem and its application to real-time strategy games. In: Ninth Artificial Intelligence and Interactive Digital Entertainment Conference. 2013.
Conference proceedings: Artificial Intelligence and Interactive Digital Entertainment Computational Intelligence and Games Last update: Holan Tomáš, RNDr., Ph.D. (09.05.2024)
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Respective algorithms will be presented theoretically during lectures; these will be implemented and empirically evaluated during labs. Last update: Holan Tomáš, RNDr., Ph.D. (09.05.2024)
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Knowledge of algorithms presented during lectures Last update: Holan Tomáš, RNDr., Ph.D. (09.05.2024)
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Environment of strategic video games from the artificial intelligence point of view Monte-Carlo Tree Search algorithm and its variants and modifications Search algorithms working with durative actions - Alpha-Beta Considering Durations, Monte-Carlo Tree Search Considering Duration Script space and scripts exploiotability; Portfolio Greedy Search, Nested Greedy Search Path-planning: steering rules, A*, HPA* Environment representation: affordances, smart objects, nav-mesh, way-points, sensory versimilitude Performant implementation of search algorithms Last update: Dvořák Tomáš, doc. RNDr., CSc. (18.09.2024)
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