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AI Algorithms
Petrželka, Jan ; Hrubý, Martin (referee) ; Janoušek, Vladimír (advisor)
This master's thesis describes artificial intelligence algorithms based on the book Artificial Inteligence: A Modern Approach by S. Russel and P. Norvig and implementation of the algorithms in the Squeak Smalltalk programming language with object oriented approach. Algorithms are based on pseudocode in the book and existing implementations in Lisp, Python and Java language. Main concepts are intelligent agents, agent simulation environments, state space search, game playing, planning, uncertainty and learning.
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Reducing Complexity of AI in Open-World Games by Combining Search-based and Reactive Techniques
Černý, Martin ; Brom, Cyril (advisor) ; Dignum, Frank (referee) ; Pilát, Martin (referee)
Open-world computer games present the players with a large degree of freedom to interact with the virtual environment. The increased player freedom makes open-world games a challenging domain for artificial intelligence. In this thesis we present three novel techniques to handle various types of complexity inherent in developing artificial intelligence for open-world games. We developed behavior objects that extend the well-known concept of smart objects and help in structuring codebase for reactive reasoning, we propose and implement constraint satisfaction techniques to specify behavior from a global viewpoint and we have shown how adversarial search techniques can mitigate the need for complex reactive decision mechanisms when a large number of parameters has to be taken into account. The general techniques are implemented and evaluated in the context of a complete open-world game Kingdom Come: Deliverance. Powered by TCPDF (www.tcpdf.org)
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Bidirectional heuristic search
Hřebejk, Tomáš ; Vyskočil, Tomáš (advisor) ; Zajíček, Ondřej (referee)
The purpose of this bachelor thesis is to summarize the most important results on bidirectional heuristic search and to bring some new thoughts. Two algorithms are described which attempt to improve the best algorithms in this field. The algorithms were experimentally compared with a unidirectional algorithm. According to the result of the comparison, we can state that bidirectional heuristic algorithms can be much faster than unidirectional heuristic algorithms. The text also describes how to solve some problems by shortest-path algorithms and how to make a good heuristic. A program which can solve a generalized puzzle was created as a demonstration.
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Reducing Complexity of AI in Open-World Games by Combining Search-based and Reactive Techniques
Černý, Martin ; Brom, Cyril (advisor) ; Dignum, Frank (referee) ; Pilát, Martin (referee)
Open-world computer games present the players with a large degree of freedom to interact with the virtual environment. The increased player freedom makes open-world games a challenging domain for artificial intelligence. In this thesis we present three novel techniques to handle various types of complexity inherent in developing artificial intelligence for open-world games. We developed behavior objects that extend the well-known concept of smart objects and help in structuring codebase for reactive reasoning, we propose and implement constraint satisfaction techniques to specify behavior from a global viewpoint and we have shown how adversarial search techniques can mitigate the need for complex reactive decision mechanisms when a large number of parameters has to be taken into account. The general techniques are implemented and evaluated in the context of a complete open-world game Kingdom Come: Deliverance. Powered by TCPDF (www.tcpdf.org)
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Risk
Štola, Miroslav ; Cibulka, Josef (advisor) ; Forst, Libor (referee)
The main goal of this thesis is to implement a strategy board game called Risk with modified rules and to create an artificial intelligence. It is possible to play the game in the hot-seat mode on one computer in case of multiple human players. The artificial intelligence is based on a search tree. Additi- onally, a straightforward artificial intelligence was created. Both AI players are tested against one another and also against human players. At the end of the thesis the results are presented and discussed. 1
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Bidirectional heuristic search
Hřebejk, Tomáš ; Vyskočil, Tomáš (advisor) ; Zajíček, Ondřej (referee)
The purpose of this bachelor thesis is to summarize the most important results on bidirectional heuristic search and to bring some new thoughts. Two algorithms are described which attempt to improve the best algorithms in this field. The algorithms were experimentally compared with a unidirectional algorithm. According to the result of the comparison, we can state that bidirectional heuristic algorithms can be much faster than unidirectional heuristic algorithms. The text also describes how to solve some problems by shortest-path algorithms and how to make a good heuristic. A program which can solve a generalized puzzle was created as a demonstration.
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AI Algorithms
Petrželka, Jan ; Hrubý, Martin (referee) ; Janoušek, Vladimír (advisor)
This master's thesis describes artificial intelligence algorithms based on the book Artificial Inteligence: A Modern Approach by S. Russel and P. Norvig and implementation of the algorithms in the Squeak Smalltalk programming language with object oriented approach. Algorithms are based on pseudocode in the book and existing implementations in Lisp, Python and Java language. Main concepts are intelligent agents, agent simulation environments, state space search, game playing, planning, uncertainty and learning.
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