| Abstract: |  My bachelor thesis studies, develops and implements algorithms for on-line learning and generating of sequential patterns primary gathered from the surrounding environment perceived by the artificial creature. Consequently it analyzes the usability of these algorithms on processing of the large data sets and on the prediction of events observed by the autonomous agent in the virtual environment. Implemented algorithms are compared to the existing algorithms, which are applicable for the similar problem.
The main objective of my work is to develop independent subsystem capable of processing incoming information and recognizing the sequential patterns behind it. These patterns are consequently used to predict upcoming events by depending on information gathered in the past. The resulting program coded in Java programing language is part of the library for on-line sequential mining and prediction developed by me. In addition I programed module compatible with the robotic operating system using ROS Java library. It can be hosted as a process called ROS node with the ability of exchanging information with other processes implementing ROS node API. In this way it can be connected into
the hybrid artificial neural network.
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