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Artificial Intelligence for Spelunky Computer Game
Závorka, Kamil ; Gemrot, Jakub (advisor) ; Ježek, Pavel (referee)
Spelunky is one of the desktop games, where player control agent in labyrinth and his task is to reach the exit. In this labyrinth there are many threats and quests, which makes the game interesting for making artificial intelligence, that can be adjusted for these threats and quests. The goal of this work was to create a framework for comfortable programming of artificial intelligence for this game. Although there is a tool named SpelunkBotAPI for its writing and executing, the API of this tool provides only basic controlling of agent and it is hard to use it. The approach, that I chose for this work, used the existing API and built a framework above it, that will be easier to use. For more intuitive using of the framework, this work crates GOAP (Goal Oriented Action Planner), that uses its functionality for reaching goals specified by the programmer.
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Turn-Based Game in 2D Grids using PDDL-based Simulator
Macke, Jaroslav ; Gemrot, Jakub (advisor) ; Brunetto, Robert (referee)
PDDL is language, that is used to write planning problems. In this thesis, we deal with how to use PDDL as the language for the creation of simulation games, especially the creation of games in a 2D grid. We will find out, that PDDL is not complex enough for those games, because of it is missing element of random elements. So we will create the extension of classic PDDL, where we will add random elements and other functions that will make writing games easier. We will implement the program that will create the simulation of a game with interactive visualization from PDDL and configuration file. In this framework, we will create several examples of games. 1
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Classic Card Games
Mifek, Jakub ; Gemrot, Jakub (advisor) ; Bída, Michal (referee)
Although there are libraries simplifying creation of card games, only few of them provide general and comprehensive design that facilitates creation of any classic card game. Our library enables simple development of card games and their graphic representation. As part of all-in-one solution we created a client-server application that is able to run any card game created using our library. To evaluate our library we implemented five exemplary games. We also created self-learning artificial intelligence that should be able to learn any classic card game implemented using our library with minimal developer's input. For our artificial intelligence we chose Q-Learning method. We hope that our project will enable simple and effective card game development and distribution to the gaming community.
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Adversarial Search in First-Person Shooter Video Game Duels
Wirth, Martin ; Gemrot, Jakub (advisor) ; Pergel, Martin (referee)
Title: Adversarial Search in First-Person Shooter Video Game Duels Author: Martin Wirth Department: Department of Software and Computer Science Education Supervisor: Mgr. Jakub Gemrot, Ph.D., Department of Software and Computer Science Education Abstract: The complexity of artificial intelligence required for modern games is getting unmanageable. Therefore, we are seeking for techniques allowing easy creation of a complex artificial intelligence. Adversarial search has become such a technique in the area of board games. Recently, an idea to apply adversarial search on other kinds of games has come up. Though, in the area of First-person shooters, no experiments examining this idea has been done yet. This thesis offers such an experiment, concerning the Deathmatch mode of two players. Our results show that the basic implementation of adversarial search is not very successful. However, it has some potencial which should be further examined. Another con- tribution of this thesis is creation of a framework which significantly simplifies further experimenting in this area. Keywords: adversarial search, duels, video games, first-person shooters 1
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Visualisation of particular algorithms using XML
Futó, Viktor ; Pergel, Martin (advisor) ; Gemrot, Jakub (referee)
The subject of this bachelor thesis is a design and implementation of a tool that visualizes particular numerical algorithms. The tool proposes a visualization environment that allows a user to write a numeric algorithm using a suggested XML language and then allowing them to animate the algorithm on the random dataset step by step. XML is a language intended for data exchange and document publishing, but as a result of its wide applicability it has established itself in many other areas. Because of its progressivity we try to use it as a programming language for writing algorithms. The application is programmed in the Ruby on Rails and React frameworks and uses the Nokogiri library to parse XML language. The usage of application is demonstrated on numerical algorithms of simulated annealing, power iteration method and method of gradient descent, in which in particular we demonstrate the application's ability to visualize steps of the algorithm also on the functions of two variables.
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Artificial Intelligence for Go on Non-standard Topologies
Červeň, Martin ; Gemrot, Jakub (advisor) ; Brunetto, Robert (referee)
Go is a popular strategic game for two players. It is usually played on a squared board of 19x19. The aim of this thesis is to create an application allowing a user to play Go on any board defined by a graph, such as sphere and torus. We created a web based client-server application, written in JavaScript and Node.js, that is using protocol Websockets for fast communication. Application allows user to play against other players on the Internet. Server can support multiple concurrent games at the same time. Boards can be created by modelling tool Blender and then imported into the application. Our application supports 3D rendering of these boards in web client using WebGL. It has responsive control, allowing changes of view by rotating, moving and zooming. Users can also play against artificial intelligence. 1
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Psychological Experiment in Virutal Reality
Kotěšovcová, Tereza ; Gemrot, Jakub (advisor) ; Bída, Michal (referee)
Title: Psychological Experiment in Virtual Reality Author: Tereza Kotěšovcová Department: Department of Software and Computer Science Education Supervisor: Mgr. Jakub Gemrot, Ph.D. Abstract: There were many experiments conducted in real environment studying the psychological effect called social facilitation. It describes changes in human behavior caused by the mere presence of other human. Usually the tested person performs a task while being watched by this other human and his performance is measured. For easy or well-known tasks, the performance is expected to be higher (social facilitation). On the other hand, for complex or novel tasks the performance gets lower (social inhibition). Our goal was to create a program, which allows us to conduct this experiment in virtual environment - the observer will be a virtual agent controlled by computer. The experiment can be configured, for example the agent behavior or content of the task can be changed. If proven true the findings about social facilitation caused by virtual humans could be relevant in areas such as computer games development or interface design. Keywords: virtual reality, psychological experiment, HTC Vive
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Procedural 2D Map Generation for Computer Games
Nepožitek, Ondřej ; Gemrot, Jakub (advisor) ; Holan, Tomáš (referee)
In some video games, levels are procedurally generated to increase game's replayability. However, such levels may often feel too random, unbalanced and lacking an overall structure. Ma et al. (2014) proposed an algorithm to solve this problem. Their method takes a set of user-defined building blocks as an input and produces layouts that all follow the structure of a specified level connectivity graph. The algorithm is based on two main concepts. The first one is that the input graph is decomposed into smaller chains and these are laid out one at a time. The second one is that configuration spaces are used to define valid relative positions of building blocks. In this thesis, we present an implementation of this method in a context of 2D tile-based maps. We enhance the algorithm with several new features, one of them being a mode to quickly add short corridors between neighbouring rooms. We also propose speed improvements, including a smarter decomposition of the input graph and tweaks of the stochastic method that is used to lay out individual chains. The resulting algorithm is able to quickly produce diverse layouts, which is demonstrated on a variety of input graphs and building blocks sets. Benchmarks of our algorithm show that it can achieve up to two orders of magnitude speedup compared to the original...
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Artificial Intelligence for the Risk Game
Vašátko, Viktor ; Pilát, Martin (advisor) ; Gemrot, Jakub (referee)
The aim of this work is the implementation of the game Risk and ex- ploration how to develop artificial intelligence into game. Game implementation and artificial intelligence experiments are written in C# programming language. Two approaches are tested in the development of artificial intelligence. One ap- proach uses the Monte Carlo tree search algorithm (MCTS) with two different heuristics and the other tries to solve the problem with neural networks. Neural networks have two uses. One use is for the artificial intelligence itself and the se- cond use is in one of the heuristics. Through the research, we found that the best player is the artificial intelligence using MCTS, but on big maps it has problem. On the other hand, the artificial intelligence with neural network can play on any map and therefore could potentially be another aim of research. The result of the work is the basis for further development of artificial intelligence. 1
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Hearthstone Counter-Deck Builder
Stachura, Šimon ; Gemrot, Jakub (advisor) ; Pilát, Martin (referee)
1 Title: Hearthstone Counter-Deck Builder Author: Šimon Stachura Department: Katedra softwaru a výuky informatiky Supervisor: Mgr. Jakub Gemrot, Ph. D. Abstract: Collecting cards and building decks out of them is the basic principle of collectible card games (such as Hearthstone). This task is usually very complex and requires players to think about a lot of factors, such as stability of deck's results or interactions among cards. The goal of this work is to try to make deckbuilding for Hearthstone automatic. Hill-climbing algorithm was used for this task. Generated decks were evaluated based on their winrate against chosen human-built actual decks from the game. Usage of hill-climbing brought a lot of questions - for instance, how to restrict the huge space of possible decks, what artifical intelligence to use for games' simulation, or how to make the simulation stable enough in such a non- deterministic environment. We have also tried to apply a new approach to a few of these problems. We have conducted two experiments to test our approach. Both experimentally created decks reached about 80 percent winrate against human-made decks. The results proved that even in such a nondeterministic environment hill- climbing is able to find interesting solutions. However, these solutions are highly dependent on...
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