Computational intelligence, referring to the ability of a computer to learn a specific task from experimental observation or data, includes theory, application, design and development of biologically and linguistically motivated computational paradigms. Computational intelligence is often known as a set of computational approaches and methodologies inspired by nature so that complex real-world problems can be addressed in the situation of which traditional modeling may not be useful due to the complexity of the processes with regard to mathematical reasoning, uncertainties inherent in such processes as well as stochastic nature of the processes. Such complexities show that it is not possible to translate many real-life problems into binary language of 0 and 1 so that computers can process them. At that stage, computational intelligence can provide solutions to such problems.
To be able to address the complex problems, computational intelligence employs an array of complementary means such as fuzzy logic (enabling the computer to understand natural language), Artificial Neural Networks (ANNs) (allowing the system to learn experiential data through the operation of biological ones), evolutionary computing (based on natural selection to process computation and solve optimization problems through the generation, evaluation and modification of a population of possible solutions), and so on. Natural selection, probabilistic methods and learning theory are mostly resorted to for tackling uncertainty and imprecision.
Computational intelligence is related to discovery science that puts emphasis on the analyzing of large volumes of experimental data or text-based data for the sake of finding new patterns or correlations. Information extraction and web mining are also closely related to examine concepts and their relationships in a natural language text as well as from databases. Another relation is in web intelligence, which is the application of Artificial Intelligence (AI) to the next generation web services and resources. Semantic web is also a related concept as the extension of the World Wide Web where web content is conveyed in a form accessible to programs like software agents.
Machine learning in knowledge-based systems is also another focal component of computational intelligence as knowledge-based systems attempt to render expertise available for purposes like decision-making and information sharing when need be. With learning based on real-world data, key challenges emerge like the decomposition of practical problems into multiple learnable components, interaction between components as well as the application of appropriate learning algorithms.
Given these affordances and means, computational intelligence provides benefits in various aspects with relation to Artificial Intelligence (AI) systems like enhanced problem-solving, decision-making, automation, optimization and adaptability, among other ones. For the other related details, one may refer and see.
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