Towards a theory of Hybrid Intelligent Autonomous Systems

Today, researchers have at their disposal, the required hardware, software, and sensor technologies to build intelligent autonomous systems. More, they are also in possession of some computational tool such as Fuzzy Logic(FL), Neural Networks (NN), Expert system(ES), Genetic Algorithms (GA) and other more technologies that are more effective in the design and development of intelligent autonomous systems than the predicate logic based methods of traditional Artificial Intelligence. FL, ES, NN, and GA are well established as useful technologies that complement each other in powerful hybrid system for example. Hybrid intelligent systems are now part of the repertoire of computer systems developers and important research mechanisms in the study of Artificial Intelligence. The integration of these technologies has proven to be a way to develop useful real-world applications, and hybrid systems involving robust adaptive. More, these theories and applications provide a source linking all fields in which intelligent control plays a dominant role. Cognition, perception, action, and learning are es2sential components of suchsystems and their use is tending extensively towards challenging applications. Key-Words: Expert System (ES), Fuzzy Logic( FL), Neural Networks (NN), Hybrid Intelligent Systems, Autonomous Systems.