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Detection of Influential Individuals, Communities, and Link Prediction in Social Networks
König, Matúš ; Mrázová, Iveta (advisor) ; Hric, Jan (referee)
Social network analysis provides several means to better understand the structure of the underlying social networks. This thesis is focused on the area of community detection in social networks. We discuss six of the main community detection algorithms and their hybrid variants involving a com- bination of rough and fine partitioning techniques. The text explains the measures used to quantify the detected communities' properties. For dif- ferent problem sizes, the Zachary's karate club and Enron email datasets were used. Further, the work concentrates on experiments that provide per- formance assessment for the investigated methods. Based on the obtained results, we draw conclusions towards recommendations for a reliable usage of the findings in practice. At the same time, we aim to identify the appropriate number of communities in the data at hand since this is a parameter of many community detection algorithms. For the same reason, we also investigate whether non-hierarchical clustering algorithms could be used to form a sub- community hierarchy. All of the mentioned experiments were run by means of a community detection system CGAT - Config-based Graph Analysis Tool we developed and implemented as a part of the thesis.
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Road Maintenance Planner (RoMaP) - Road Traffic Simulator
Zelený, Marek ; Ježek, Pavel (advisor) ; Hric, Jan (referee)
The goal of this thesis was to create a tool that would allow municipal administration to measure the effects of traffic restrictions. This would help with planning (especially parallel) road maintenance, minimising the effects on traffic fluency. Our main focus was to find a compromise between simplicity of usage and sufficient detail for reasonably accurate results. Rather than copying the effort of some existing so- lutions which provide incredibly detailed simulations, we tried to come up with a different approach offering just the right information for this particular use-case. With this in mind, we developed a Windows Forms application for simulating traffic flow on a road network. The application provides graphical interface for creating maps and running simulations on them. The user can observe the simulation through various graphical elements and charts, as well as preform data analysis on collected statistics afterwards. 1
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Reactive Programming with Events
Petříček, Tomáš ; Syme, Don (advisor) ; Hric, Jan (referee)
The reactive programming model is largely different to what we're used to as we don't have a full control over the application's control flow. As a result, reactive applications need to be structured differently and need to be written using different patterns. We build an easier way for developing reactive applications. Our work integrates declarative and imperative approach to reactive programming and uses the notion of event as the unifying concept. We discuss the problem of memory management in this scenario and develop a technique for collecting not only events that are not reachable, but also events that cannot trigger any action. Next, we present a language extension that makes it possible to wait for occurrences of events that match some defined pattern. The extension isn't bound to the reactive programming model and can be used for concurrent and parallel programming scenarios as well. Finally, we develop a reactive programming library that builds on top of the ideas discussed earlier and we present semantics of the library to enable formal reasoning about reactive programs.
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MCTS for the game Metro
Venta, Václav ; Hric, Jan (advisor) ; Babka, Martin (referee)
MCTS method was first introduced in 2006 and it immediately succeeded in the game of GO. Its biggest advantage is that it doesn't require any evaluation function, which is often hard to design in a lot of games. Instead it is based on randomized simulations. This thesis describes MCTS principles and deals with its suitability for the board game Metro. The text describes Metro characteristics which make the game suitable for the use of MCTS. A software serving as game environment is attached to this work on CD. It has artificial intelligence based on MCTS method implemented in it. Powered by TCPDF (www.tcpdf.org)
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Applications of Patterns in Game Go
Hamplová, Romana ; Hric, Jan (advisor) ; Majerech, Vladan (referee)
This work implements a solver for tactical goals in the game of Go (capturing stones, connecting groups). The solver is based on recognizing the shapes of stones on the desk and choosing the moves from prede ned database of patterns and the follow-up moves. The main part of this work features analysis and proposal of convenient representation of patterns which follow typical situations in the game and their solving considering both the attacker and the defender. User interface of the program allows execution of the solver including selection of the type of the tactical goal, creating new patterns and editing the whole database of patterns. The work also contains a precreated pattern database and examples of use.
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MCTS with Information Sharing
Baudiš, Petr ; Hric, Jan (advisor) ; Majerech, Vladan (referee)
We introduce our competitive implementation of a Monte Carlo Tree Search (MCTS) algorithm for the board game of Go: Pachi. The software is based both on previously published methods and our original improvements. We then focus on improving the tree search performance by collecting information regarding tactical situations and game status from the Monte Carlo simulations and sharing it with and within the game tree. We propose specific methods of such sharing --- dynamic komi, criticality-based biasing, and liberty maps --- and demonstrate their positive effect. based on collected play-testing measurements. We also outline some promising future research directions related to our work.
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Introduction of Castes in Evolution of Artificial Beings
Trunda, Otakar ; Hric, Jan (advisor) ; Holan, Tomáš (referee)
In present work we study questions about introduction of castes in evolution of artificial beings. We present the concept that allows defining various castes and its mutual relations and simulating life of members of these castes in virtual environment. We describe features of our concept and illustrate its usability on several typical scenarios using castes. In this environment we study model situations where the beings in virtual world play different roles. We observe the simulations and its results trying to learn what impact the initial conditions, agents parameters (such as Life expectancy) and environment parameters (e.g. mutation probability) have on the outcome of the simulation.
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Sound Processing in an Emulator of Cochlear Implant
Tóth, Peter ; Maršálek, Petr (advisor) ; Hric, Jan (referee)
The time accuracy of the auditory neuronal pathway in its sound localization branch is high, compared to other sensory systems. The time differences in the sound arrival between the left and right ear are distinguished by the neural circuit in this branch. The accuracy achieved here is in the order of tens of microseconds. This phenomenon has not yet been definitively clarified. In this master thesis, a model of a neuron central to this neural circuit is presented. This neuron is called binaural (neuron of the two ears) and is located in the medial superior olive (MSO) neural nucleus. The properties of the MSO neuron are described. Specifically, the neuron acts as a coincidence detector, and this is necessary for the circuit functioning. Main result of the thesis is the theory explaining how the function of the coincidence detector can be described based on the interaction of the post-synaptic potentials on the spike-response model neuron. Generality and implications for the auditory pathway are then discussed.
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Genetic Algorithms driven by MCTS
Havránek, Štěpán ; Hric, Jan (advisor) ; Moudřík, Josef (referee)
Evolutionary and genetic algorithms are problem-solving methods designed according to a nature inspiration. They are used for solving hard problems that we cannot solve by any efficient specialized algorithm. The Monte Carlo method and its derivation the Monte Carlo Tree Search (MCTS) are based on sampling and are also commonly used for too complex problems, where we are dealing with enormous memory consumption and it is impossible to perform a complete searching. The goal of this thesis is to design a general problem solving method that is built from these two completely different approaches. We explain and implement the new method on one example problem: the Traveling salesman problem (TSP). Second part of this thesis contains various tests and experiments. We compare different settings and parametrizations of our method. The best performing variant is then compared with the classical evolutionary TSP solution or, for example, with greedy algorithms. Our method shows competitive results. The best results were achieved with the cooperation of our method and the classical evolutionary TSP solution. This union shows better results than any of its parts separately, which we find as a great success.
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City-building game
Hejda, Benjamin ; Malenko, Jaromír (advisor) ; Hric, Jan (referee)
Present work describes the Sword of Damocles application. It is a citybuilding strategy game, where player's task is to care about some city and wellbeing of its inhabitants. Main goal of the work was to design and implement a control that would allow to govern the city in detail and e ectively at once. That was achieved by system of parameters set as expressions referencing other parameters and city describing indicators. Substantial feature of the game are independently acting people that can not be directly controlled. Part of the program is a scenario editor that makes the gameplay widely customizable. The graphical user interface is very simple, however, it is possible to change it not a ecting core of the application.
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