Abstract
The term intelligent systems is used to describe the necessary level of performance required to achieve the system goals. Intelligence has been observed and scientifically categorized as a biological stimuli response mechanism that is provided to satisfy an intended activity.Intelligence considers cognitive aspects of human behaviour, such as perceiving, reasoning, planning, learning, communicating and innovation. As society evolved, innovative individuals invented tools to assist them in achieving better outcomes. Since the industrial revolution [1], science and mechanization have become central to many academic challenges, driving a paradigm shift from philosophy towards systems engineering techniques. This desire to improve mechanized systems created the need for improvements to automation processes. These achievements extend the pioneering efforts of others stimulating new research and developments [2]. Computational Intelligence(CI) has evolved over the past 60 years [3] with many new fields of study emerging to dissolve obstacles encountered. These attempts relate to efforts at personifying attributes of human behavior and knowledge processes within machines. The resulting Machine Intelligence [4,5] efforts stimulated the study of Artificial Intelligence(AI) [6,7] and led to the evolution of many contemporary techniques.
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Tweedale, J.W., Jordanov, I. (2013). An Introduction to Contemporary Achievements in Intelligent Systems. In: Jordanov, I., Jain, L.C. (eds) Innovations in Intelligent Machines -3. Studies in Computational Intelligence, vol 442. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32177-1_1
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