This thesis deals with the placement of irregular shapes on a fixed width plane, which is a problem whose solution can be used, for example, when placing sewing patterns on fabric so that its length is as small as possible. A continuity of shapes depending on ma- terial patterns are also taken into account. The thesis uses evolutionary algorithms with heuristic functions that assign positions to individual shapes depending on the individual being developed by the relevant evolution. Patterned fabrics are treated differently using special heuristic functions types that are able to adjust the layout. 1

The background research in this Master’s thesis is focused on swarm intelligence. Further, there are two experiments described. They are based on released publications and they study behaviour of a group of robots during a puck gathering and during a target search. The actual thesis follows a repetition of these experiments in Microsoft Robotics Developer Studio (RDS), a free robotics simulation environment. The realization of both experiments in RDS is documented in detail and the achieved results are evaluated and compared with the results described in the publications. In conclusion, the thesis summarizes basic features, advantages and disadvantages of developing in RDS, based on a personal experience.

Diplomová práce se zabývá problematikou použití umělé inteligence v managementu rizik v kontextu malé výrobní společnosti Princ parket. Práce představuje společnost a přináší analýzu rizik, která vede k rozhodnutí zaměřit se na riziko poškození dobrého jména z důvodu produkce vadných výrobků. Jejím výsledkem je poskytnutí vyvinutých nástrojů RETUNN využívající metod Neuronových sítí, které umožňují predikci rizika a následnou implementaci opatření na snížení tohoto rizika.

This master thesis deals with issues connected with using artificial intelligence in metal exchange. It describes theoretical bases of financial markets, various methods of analyses and artificial intelligence. Main accent is put on creating functional models in Matlab program which will predicate incoming values of time series. Part of the thesis is description of company, for which are those models of neural networks for supporting decision making created.

Designing and creating the finished OLAP solutions within Business Intelligence for an undertaking by the customer's requirements using standard technologies and practices that are designed for this purpose. This work describes the work of the design, creation and deployment of the finished project Business Intelligence solution that allows the customer to perform more accurate analysis of their own data in the context of controlling.

The diploma thesis is focused on the evaluation of inforamtion systems of selected company with the support of Business Intelligence tools in the field of economical and financial risks. Theoretical points are focused on the use of new trends in the field of BI. Further theoretical part is the area of risk management. The practical part will analyze the current state of a particular company. The aim is to design analytical and reporting support services with Business Intelligence tools in financial risk for their effective assessment and management.

This thesis deals with scheduling problems and algorithms usable to solve them. Scheduling algorithms seek an optimal allocation of resources over time while using constraints. Scheduling problems are often different in nature and type of constraint conditions. In the practical part is solved one particular type of scheduling problem, which is a constrained version of the common scheduling problem.

As information and communication technology develops swiftly, amount of information produced by various sources grows as well. Sorting and obtaining knowledge from this data requires significant effort which is not ensured easily by a human, meaning machine processing is taking place. Acquiring emotion from text data is an interesting area of research and it’s going through considerable expansion while being used widely. Purpose of this thesis is to create a system for positive and negative emotion detection from text along with evaluation of its performance. System was created with Java programming language and it allows training with use of large amount of data (known as Big Data), exploiting Spark library. Thesis describes structure and handling text from database used as source of input data. Classificator model was created with use of Support Vector Machines and optimized by the n-grams method.

Procedural Content Generation is now used in many games to generate a wide variety of content. It often uses players controlled by Artificial Intelligence for its evaluation. PCG content can also be used when training AI players to achieve better generalization. In both of these fields, evolutionary algorithms are employed, but they are rarely used together. In this thesis, we use the coevolution of AI players and level generators for platformer game Super Mario. Coevolution's benefit is, that the AI players are evaluated by adapting level generators, and vice versa, level generators are evaluated by adapting AI players. This approach has two results. The first one is a creation of multiple level generators, each generating levels of gradually increased difficulty. Levels generated using a sequence of these generators also mirror the learning curve of the AI player. This can be useful also for human players playing the game for the first time. The second result is an AI player, which was evolved on gradually more difficult levels. Making it learn progressively may yield better results. Using the coevolution also doesn't require any training data set.

This master thesis deals with the topic of surveillance while focusing on its technological extensions. Particular focus will be primarily on the topic of artificial intelligence, which is currently one of the most important technologies in the field of computer science. My intention for this work will be to introduce artificial intelligence and to offer an insight into its application in surveillance studies and thus combine theoretical and technological thesis together. The thesis will be divided into five parts - the first part introduces research questions, methodology and division of the whole work, the second part will briefly introduce surveillance and its study, the third part will introduce artificial intelligence, its history, present and, above all, the outlook for the future, and the fourth part will link those two fields together.The last, fifth, part offers a reflection and answer to the question of what future awaits us in the proces of implementation of artificial intelligence in the field of surveillance.