Intelligent Agent Control Using Inductive, Deductive and Case Based Reasoning

The paper deals with the problem of intelligent system’s design for complex environments. A possibility to integrate several technologies into one basic structure that could form a kernel of an intelligent system or intelligent agent has been discussed. An alternative structure is proposed in order to form the 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 adaptation 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 (intelligent entities). This paper discusses a possibility to use the proposed structure in order to model intelligent entities or entire intelligent systems for hardly predictable environments or environments with stochastic features in agent based modeling domains [Ref. 18,19]. The basic elements of the proposed structure have found their implementation in a software system and an experimental robotic system. The software system as well as the robotic system have been used for experimentation in order to validate the proposed structure its functionality, flexibility and reliability. Both of them are shortly 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.