Since the invention of computers and other similar machines, scientists and researchers have been trying very hard to enhance their capabilities to perform various tasks. As a result, the capabilities of computers are growing exponentially day by day in terms of diverse working domains, versatile jobs, processing speed, and reduced size. Now, we are in the race to make these machines as intelligent as human beings. Artificial intelligence (AI) came up as a way of making a computer or computer software think in a similar manner to the way that humans think. AI is inspired by the study of human brain, including how humans think, learn, decide, and act while trying to solve a problem. The outcomes of this study are the basis of developing intelligent software and systems or intelligent computing (IC).

An IC system has the capabilities of reasoning, learning, problem-solving, perception, and linguistic intelligence. IC systems consist of AI techniques as well as other emerging techniques that make a system intelligent. The use of IC has been seen in almost every sub-domain of computer science such as networking, software engineering, gaming, natural language processing, computer vision, image processing, data science, robotics, expert systems, and security. Nowadays, IC is also useful for solving various complex problems in diverse domains such as for predicting disease in medical science, predicting land fertility or crop productivity in agricultural science, predicting market growth in economics, and weather forecasting.

For all these reasons, this book presents the advances in AI techniques, under the umbrella of IC. In this context, the book includes recent research that has been done in the areas of machine learning, neural networks, deep learning, evolutionary algorithms, genetic algorithms, swarm intelligence, fuzzy systems, and so on. This book discusses recent theoretical, algorithmic, simulation, and implementation-based advancements related to IC.

About the Author

Anshul Verma, Lalit Garg

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