National Repository of Grey Literature 177 records found  1 - 10nextend  jump to record: Search took 0.00 seconds. 
Coalition Games in a Dynamic Multiagent Environment
Hamran, Peter ; Uhlíř, Václav (referee) ; Zbořil, František (advisor)
The essence of this bachelor thesis was to implement an algorithm for suitable coalition forming in multi-agent system. Suitable coalition denotes a coalition which is not formed in super-additive environment and so it depends on its size and members. Aim of this thesis was to adjust an algorithm for coalition bounds forming between agents in a way, that it is applicable in a multi-agent competition MASSIM. Key aspects are amount of messages sent between agents for coalition to form and also a time it takes to calculate all coalitional values required for such a process. Final scenario is where two competitive groups of agents compete for resources in a multi-agent system simulation.
Coalition Formation in Multiagent Systems Using Genetic Algorithms
Kučera, Tomáš ; Uhlíř, Václav (referee) ; Zbořil, František (advisor)
This thesis discusses the basics of software agents and the way they form the multiagent coalitions. Genetic algorithms are introduced as one of the methods of solving the coalition formation problem. MAPC 2018 competition is introduced, which inspired the final design and implementation of the solution by using the tools described. A demo project was created, in which agents communicate with the MASSim server and gather data which is then used as an input into the genetic algorithm. Its purpose is to assign the agents to the tasks based on the input data, so that the tasks can be accomplished in the most effective manner possible. The results of this algorithm are evaluated in experiments which are focused on the quality of the solutions found as well as the time required for the calculation.
Interconnection of Recent Strategic Games with Multi-Agent Frameworks
Válek, Lukáš ; Kočí, Radek (referee) ; Zbořil, František (advisor)
This thesis is focused on design of framework for creation an articial opponents in strategy games. We will analyze different types of strategy games and artificial intelligence systems used in these types of games. Next we will describe problems, which can occur  in these systems and why agent-based systems makes better artificial opponents. Next we will use knowledge from this research to design and implement framework, which will act as support for creating an artificial intelligence in strategy games.
Strategic Game Based on Multiagent Systems
Knapek, Petr ; Kočí, Radek (referee) ; Zbořil, František (advisor)
This thesis is focused on designing and implementing system, that adds learning and planning capabilities to agents designed for playing real-time strategy games like StarCraft. It will explain problems of controlling game entities and bots by computer and introduce some often used solutions. Based on analysis, a new system has been designed and implemented. It uses multi-agent systems to control the game, utilizes machine learning methods and is capable of overcoming oponents and adapting to new challenges.
Program for Interactive Family-Tree Making
Navrátilová, Eva ; Zbořil, František (referee) ; Rozman, Jaroslav (advisor)
This thesis describes the design and implementation of an application for interactive family-tree making. The application supports importing and exporting data in GEDCOM format, further editing of the data, visualizing the data in family charts and their export. The design of the program is modular. It is implemented using C++ and Qt. The program was released for testing amongst the group of Czech and Slovak genealogists and their opinions on the program were obtained and analysed.
Computer Aided Transformation of Guitar Solos from Recorded Song to Tabs
Joščák, Juraj ; Veigend, Petr (referee) ; Zbořil, František (advisor)
The aim of this thesis was automatic pitch detection in melodic guitar lines and subsequent transcription to guitar tablature. Final system uses comb filtering to detect pitch. Individual notes are separated by beat detection. An algorithm for transcription of notes to guitar tablature, based on minimalization of hand movement is proposed.
Semi-Automatic Word Normalization in Parish Records
Hříbek, David ; Zbořil, František (referee) ; Rozman, Jaroslav (advisor)
This work deals with the extension of DEMoS web application for the management of parish records by the possibility of normalization (assignment of a normalized form of writing to individual words) of names, surnames, occupations, domiciles and other types of words occurring in parish records. In the solution, a duplicate record detection process was used, which allowed sorting of the records from parish records into clusters of similar words. As a result of the clustering, it was possible to share normalized word variants within these clusters. Thus, DEMoS suggests normalized variants for words entered by users, used not only for the same words, but also for similar words. In this work, automatic testing of word clustering was proposed. In total, 640 different combinations of clustering parameters were tested for each word type. Subsequently, the best clustering parameters were selected for each word type. By normalizing words, DEMoS application significantly increases the efficiency of searching in parish records. Records are also easier to read.
Evolutionary Algorithms for Neural Networks Learning
Vosol, David ; Rozman, Jaroslav (referee) ; Zbořil, František (advisor)
Main point of this thesis is to find and compare posibilities of cooperation between evolutionary algorithms and neural network learning and their comparison with classical learning technique called backpropagation. This comparison is demonstrated with deep feed-forward neural network which is used for classification tasks. The process of optimalization is via search of optimal values of weights and biases within neural network with fixed topology. We chose three evolutionary approaches. Genetic algorithm, differential evolution and particle swarm optimization algorithm. These three approaches are also compared between each other. The demonstrating program is implemented in Python3 programming language without usage of any third parties libraries focused on deep learning.
Universal Cloud-Based 3D Print Slicer
Vejčík, Jakub ; Zbořil, František (referee) ; Kočí, Radek (advisor)
This bachelor thesis deals with the proposal and implementation of a cloud tool for preparation 3D models for 3D printing. 3D printing become a part of our lives and it is getting into schools, where it combines the digital world with the physical world. Nowadays schools have not sufficient computational power to handle demanding 3D models for 3D printing. This ascertainment has led me to create a cloud tool, because cloud provides sufficient computational power and it can be shared beetween multiple users at the same time. The cloud tool solves the problem of insufficient power to translate 3D models to G-code, which understands 3D printer. Solution is done by letting the demanding computing logic on the cloud and user just edit model according to his ideas in the web interface of cloud tool.
Optimization Algorithms Inspired by Nature
Babjarčiková, Lenka ; Zbořil, František (referee) ; Zbořil, František (advisor)
This thesis deals with four optimization algorithms inspired by nature. It describes ant colony optimization algorithm, marriage in honeybees optimization algorithm, grey wolf optimization algorithm and simulated annealing algorithm. The main part of this thesis is the application of these algorithms for solving three optimization problems. One of the problems is travelling salesman problem, which is solved by ant colony optimization, next problem is searching for extreme of function solved by grey wolf optimization and simulated annealing algorithms and the last is boolean satisfiability problem solved by marriage in honeybees optimization algorithm. Thesis contains experiments with these algorithms and reviews gained results.

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