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Adaptive Plot Generation in Role-Playing Game
Vymazal, Jiří ; Grochol, David (referee) ; Hrbáček, Radek (advisor)
Generating a story, while trying to preserve at least some qualities of author-written narrative is a complex issue. In this thesis several currently existing systems and approaches are discussed. Then, a solution based on evolutionary computation is presented, and its traits shown on small-scale proof-of-concept scenario. Finally, this approach is compared againist existing solutions.
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Board Game Focused on Educational Support for Gaming Algorithms
Čáslava, Martin ; Hrubý, Martin (referee) ; Drahanský, Martin (advisor)
Tato práce se zabývá oblastí umělé inteligence zvané jako ''Metody pro hraní her''. Cílem této bakalářské práce je navrhnout a implementovat software, který umožní uživateli snadněji pochopit principy herních algoritmů Minimax a Alfa-beta prořezávání. Typickými uživateli tohoto softwaru mohou být například studenti oboru umělá inteligence. Práci lze rozdělit do dvou hlavních částí. První, teoretická část, se snaží vysvělit koncept ''Metoda pro hraní her'', dále obsahuje popis návrhu softwaru a popis výukových přínosů aplikace. Druhá část práce je věnována popisu implementace softwaru, testování a diskuzi dosažených výsledků.
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Strategy for Game Systems
Švestka, Marek ; Tóth, Michal (referee) ; Zemčík, Pavel (advisor)
This thesis resolves the artificial intelligence representation in computer games. The goal was to find it's suitable interpretation methods. The issue was solved with "map"implementation, which is the n-dimension matrix holding the information about current game state for the concrete player. There were various types of these matrixes used in this thesis. Furthermore was designed a way to evolve computer opponents during the gameplay and created an algorithm, that gives the idea of the space in which it is located. Benefit from this thesis is a solution that makes artificial adversary close to human gameplay behavior. The outcome could also be used in simulators for military battles in real world.
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Interface for Creation of Game Agents in Jason
Rusnák, Jakub ; Samek, Jan (referee) ; Král, Jiří (advisor)
Thesis deals with creation of interface for creating agents in Jason programming language for Unreal Tournament 2004. Reader is introduced to theory of agent systems, UnrealTournament game and GameBots environment. The paper describes design of this interface and it's implementation. It also deals with the problem of finding path for bots in game. It desribes creation of your own bot using this interface. Finally, efficiency of solution is evaluated.
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Cryptanalysis of Symmetric Encryption Algorithms Using Genetic Programming
Smetka, Tomáš ; Janoušek, Vladimír (referee) ; Homoliak, Ivan (advisor)
This diploma thesis deals with the cryptanalysis of symmetric encryption algorithms. The aim of this thesis is to show different point of view on this issues. The dissimilar way, compared to the recent methods, lies in the use of the power of evolutionary principles which are in the cryptanalytic system applied with help of genetic programming. In the theoretical part the cryptography, cryptanalysis of symmetric encryption algorithms and genetic programming are described. On the ground of the obtained information a project of cryptanalytic system which uses evolutionary principles is represented. Practical part deals with implementation of symmetric encrypting algorithm, linear cryptanalysis and simulation instrument of genetic programming. The end of the thesis represents experiments together with projected cryptanalytic system which uses genetic programming and evaluates reached results.
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Artificial Intelligence in Power Oil Transformers Diagnostics
Janda, Ondřej ; Szabó,, Radek (referee) ; Kratochvíl, Petr (referee) ; Hammer, Miloš (advisor)
This dissertation thesis deals with the application of expert systems and soft computing methods in field of power oil transformers. The main work is divided into theoretical and practical part. First, the theoretical part presents the basic elements of the transformer, and approaches to its diagnosis. The work focused mainly on the diagnostics of the insulation system, and diagnostic methods and approaches in this specific area. Next part describes the basics of expert systems and other soft computing methods such as: fuzzy logic, neural networks, genetic algorithms and their combinations and extensions. At the end of the theoretical part, the possibility of optimization approaches by means of artificial intelligence and its application in fuzzy model optimization are described. The practical part begins with description of the used data file that runs through the entire work. The work is then divided into four parts, namely in parts which deal with the expert system for transformer diagnostics, DGA module, prediction module, and optimization using artificial intelligence. The section describing the expert system gives specific information about the particular expert system. The means and techniques used for constructing given system are described, and then the complete system design and description of all subsystems and modules are presented. The next section describes the developed DGA module and all selected approaches to its implementation and expansion. At the end of the chapter, the results of comparison between all implemented methods are evaluated. The third part deals with the prediction module and describes its design and construction, including description of the main parts which are based on the selected predictive approaches. Also, the predictions of selected quantities from the data file are included. There are two predictive approaches being used: the one step prediction, and the multiple step prediction. The comparison of prediction accuracy and computational cost of given methods is presented at the end of this chapter. The last part deals with the possibilities of optimization using artificial intelligence methods, namely differential evolution, PSO, and genetic algorithms. Both the single-objective and the multi-objective optimization are considered. The methods are compared in a series of synthetic tests and then applied to optimize the fuzzy models of DGA tests from an earlier part of this work. The dissertation also includes chapters: "The Aims", "The Contribution of the Work", and a list of publications, products, and projects of the author.
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Evolutionary Optimization of Control Algorithms
Weisser, Roman ; Šeda, Miloš (referee) ; Zelinka,, Ivan (referee) ; Ošmera, Pavel (advisor)
The dissertation thesis deals with Evolution optimization of control algorithms. The first part of the thesis describes the principles and partial methods of evolution optimization methods especially those used in two-level transplant evolution method. Later the grammatical evolution method is described, which modified algorithm became impulse for creation of transplant evolution method. The transplant evolution method and its two-level modification are new evolutionary algorithms proposed in this work, which were used for optimization of structure and parameters of general controllers control algorithms. The transplant evolution algorithm and its extended two-level modification are described in detail in next chapters. The proper settings of evolutionary algorithms are important for minimization the time of optimization and for finds results approaching the global optimum. For proper setting the parameters of differential evolution was created meta-evolution algorithm that is described in chapter named meta-evolution. The basic concepts of control, chosen methods of system identification and controller parameters settings are described in next part. This part describes algorithms of digital controllers and some specific methods uses in digital control. The demonstrations of control algorithm optimizations of various types of controllers are showed in experimental part. The optimized algorithms of general controllers are compared with various types of PSD controllers which were set by various algebraic methods or differential evolution for various models of systems. In the conclusion of this work is stated a recommendation for further development of evolutionary optimization of controllers are focusing on parallel and distributed computing.
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Proposal of prediction model sales of selected food commodities
Řešetková, Dagmar ; Dostál, Petr (referee) ; Krčmarský, Miroslav (referee) ; Zelinka, Ivan (referee) ; Rais, Karel (advisor)
The dissertation is generally focused on the use of artificial intelligence tools in practice and with regard to the focus of study in the field of Management and Business Economics at using the tools of artificial intelligence in corporate practice, as a tool for decision support at the operational and tactical level management. In the narrower sense, the task deals with the proposal of the prediction sales model of selected food commodities. The proposed model is designed to serve as a substitute for a human expert in support decision-making process in the purchase of selected commodities, especially when training new staff and extend the currently used methods of managerial decision-making about artificial intelligence tools for company management and existing employees. The aim of this dissertation is the design prediction sales model of selected food commodities (apples and potatoes) for specific wholesale of fruit and vegetable operating in the Czech Republic. To become familiar with the behaviour of selected commodities were used primary and secondary research as well and knowledge gained from Czech and foreign literature sources and research. The resulting predictive model is developed using statistical analysis of time series and the sales prediction proceeds using the tools of artificial intelligence and is modeled by an artificial neural network. The dissertation in the practical part also contains proposals for the use of the prediction model and partial processing procedures for: • practice, • theory, • pedagogical activities.
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Fuzzy investment decision support for brownfield redevelopment
Brož, Zdeněk ; Čapek, Jan (referee) ; Dostál, Petr (referee) ; Fecenko, Josef (referee) ; Dohnal, Mirko (advisor)
Tato disertační práce se zaměřuje na problematiku investování a podporu rozhodování pomocí moderních metod. Zejména pokud jde o analýzu, hodnocení a výběr tzv. brownfieldů pro jejich redevelopment (revitalizaci). Cílem této práce je navrhnout univerzální metodu, která usnadní rozhodovací proces. Proces rozhodování je v praxi komplikován též velkým počet relevantních parametrů ovlivňujících konečné rozhodnutí. Navržená metoda je založena na využití fuzzy logiky, modelování, statistické analýzy, shlukové analýzy, teorie grafů a na sofistikovaných metodách sběru a zpracování informací. Nová metoda umožňuje zefektivnit proces analýzy a porovnávání alternativních investic a přesněji zpracovat velký objem informací. Ve výsledku tak bude zmenšen počet prvků množiny nejvhodnějších alternativních investic na základě hierarchie parametrů stanovených investorem.
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New Entrepreneurial Trends - Accountant Tasks Outsourcing Based on Multidimensional Decision-making
Kába, Daniel ; Koráb, Vojtěch (advisor)
The work deals with multidimensional decision-making in the outsourcing of accounting work; it is designed for accounting companies with more than 30 employees. These companies deal with hundreds of accounting tasks of various extent and nature which would be assigned to individual accountants. Theoretically speaking, the problem of assigning tasks to individual accountants can be resolved by well-known methods of operational research; however, certain qualities of accountants are very vague and are hard to quantify. These qualities include creativity, loyalty, credibility towards clients, etc. The qualities make the application of traditional algorithms (e.g. scheduling algorithms) very difficult. Moreover, certain accounting tasks are unique and can be assigned only by experienced managers, not algorithms. This work focuses on a fuzzy description of tasks and accountants and a two-level assignment process. In preliminary sorting, individual tasks to be assigned are classified as routine, which can be assigned through a fuzzy algorithm, or non-routine, which are assigned to individual employees through the manager . fuzzy expert system dialogue.
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