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Artificial inteligence and its application in the coccolith determination
Voženílková, Kristýna ; Holcová, Katarína (advisor) ; Svobodová, Andrea (referee)
Automatic determination of objects using neural networks has been applied in many fields of study, however, this approach has only rarely been used in paleontology. The goal of this bachelor thesis is to evaluate a method of automatic determination of coccoliths using neural networks. This method has been proposed by the Cogniware company. Cyclicargolithus floridanus and Cyclicargolithus abisectus have been chosen for the testing of the neural network. So far, the network has been trained to determine only C. floridanus, and managed to recognize the typical speciman of this species with 99% accuracy. This thesis provides a basic overview of the coccolith group and neural networks. It also describes the method used to prepare data for the neural network. Key words: calcareous nannoplankton, Reticulofenestra, morfology, artificial intelligence, neural network
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Space game with artificial intelligence
Bašta, Přemysl ; Pilát, Martin (advisor) ; Gemrot, Jakub (referee)
Part of this thesis consists of the implementation of my own simple space game which serves as an experimenting en vironment for testing different aproaches of artificial inteligence. There have been created abstractions in a form of sensoric methods and action plans as a transition between low leve l and high level information about game state and actions. These abstractions help algorithms of artifical inteligence with game agent manipulation. As far as algorithms are considered I chose genetic programming and Deep Q-learning as main aproachces for inteli gent agent development. Final part contains description of behaviour of developed agents and discussion of performed experiments.
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Self-Modifying Cellular Automata
Szabo, Peter ; Drábek, Vladimír (referee) ; Bidlo, Michal (advisor)
This work deals with cellular automata with a concept of self- modification and their comparsion against regular cellular automatons . For this task we constructed a simulator , that lets us define the logic of artificial inteligence, number generator and statistical test, which are used by the automata , on their own . Consequently two experiments are carried out that demonstrate the concept of self- modification .
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Application of SAT Solvers in Circuit Optimization Problem
Minařík, Vojtěch ; Mrázek, Vojtěch (referee) ; Vašíček, Zdeněk (advisor)
This thesis is focused on the task of application of SAT problem and it's modifications in area of evolution logic circuit development. This task is supposed to increase speed of evaluating candidate circuits by fitness function in cases where simulation usage fails. Usage of SAT and #SAT problems make evolution of complex circuits with high input number significantly faster. Implemented solution is based on #SAT problem. Two applications were implemented. They differ by the approach to checking outputs of circuit for wrong values. Time complexity of implemented algorithm depends on logical complexity of circuit, because it uses logical formulas and it's satisfiability to evaluate logic circuits.
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Security Game with Planning Agents
Ohman, Ľubomír ; Gemrot, Jakub (advisor) ; Hric, Jan (referee)
The goal of the thesis was to create an application for training security guards, containing a configurable artificial burglar. To fulfill these expectation, a 3D application was implemented, containing a 2D editor of security objects. In order to be able to implement the burglar, we analyzed his objectives and designed an algorithm capable of planning his actions and dealing with the multi- objective optimization. Finally, we compared the performance of our proposed solution to the state- of-the-art algorithm to prove that it solved the optimization more efficiently in our case.
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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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Word2vec Models with Added Context Information
Šůstek, Martin ; Rozman, Jaroslav (referee) ; Zbořil, František (advisor)
This thesis is concerned with the explanation of the word2vec models. Even though word2vec was introduced recently (2013), many researchers have already tried to extend, understand or at least use the model because it provides surprisingly rich semantic information. This information is encoded in N-dim vector representation and can be recall by performing some operations over the algebra. As an addition, I suggest a model modifications in order to obtain different word representation. To achieve that, I use public picture datasets. This thesis also includes parts dedicated to word2vec extension based on convolution neural network.
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Artificial Intelligence for Quoridor Board Game
Brenner, Matyáš ; Gemrot, Jakub (advisor) ; Černý, Martin (referee)
The aim of this work is to design an Artificial Intelligence for Sector 66, which is a board game based on Quoridor. In Sector 66 there is a possibility to use spells and fields with some special effects. The Artificial Intelligence is based on Monte Carlo Tree Search. It can be used for 2 to 4 players. The Artificial Intelligence introduced in this work can work with the high branching factor of Quoridor/Sector 66 Game and can also handle unknown elements represented by user defined plug-ins. The game and the Artificial Intelligence has been developed using .NET Framework, XNA and C#. Powered by TCPDF (www.tcpdf.org)
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Citadels AI
Pekárek, Jakub ; Holan, Tomáš (advisor) ; Gemrot, Jakub (referee)
The aim of this thesis is to implement a playable version of the game Citadels with console interface, and to use it for analysis of the game's properties and development of artificial intelligence. This thesis includes an analysis of strategies, a scheme for their design, an organization of turn processing, a model of intelligence implementation and testing tools. A number of approaches to specific moves have been developed, all of which achieved positive impact on overall intelligence performance. Game analysis showed a variety of game situations that need to be approached in different ways. Consequently, inappropriateness of usage of general approaches has been demonstrated; while showing benefits of the suggested inteligence design, based on a composition of separate strategies. A strong influence of player earnings on the overall performance has also been demonstrated, while other factors only show very low influence in general case. Powered by TCPDF (www.tcpdf.org)
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