Artificial Intelligence Inductive Reasoning Deductive Reasoning Case Based Reasoning Machine Learning Learning Algorithms
Institute of Information Theories and Applications FOI ITHEA
The paper deals with a problem of intelligent system’s design for complex environments. There is
discussed a possibility to integrate several technologies into one basic structure that could form a kernel of an
autonomous intelligent robotic system. One alternative structure is proposed in order to form a basis of an
intelligent system that would be able to operate in complex environments.
The proposed structure is very flexible because of features that allow adapting via learning and adjustment of the
used knowledge. Therefore, the proposed structure may be used in environments with stochastic features such
as hardly predictable events or elements. The basic elements of the proposed structure have found their
implementation in software system and experimental robotic system. The software system as well as the robotic
system has been used for experimentation in order to validate the proposed structure - its functionality, flexibility
and reliability. Both of them are presented in the paper. The basic features of each system are presented as well.
The most important results of experiments are outlined and discussed at the end of the paper. Some possible
directions of further research are also sketched at the end of the paper.