This book presents new technologies and applications in deep learning, artificial intelligence and robotics. The field of machine intelligence (MI), unifying robotics and artificial intelligence is experiencing constant growth and change. The challenge to reproduce human behavior in machines requires the interaction of many fields, from engineering to mathematics, from neurology to biology, from computer science to robotics, from web search to social networks, from machine learning to game theory, etc. This book Progresses in Artificial Intelligence & Robotics : Algorithms & Applications (proceedings of 3rd International Conference on Deep Learning, Artificial Intelligence and Robotics (ICDLAIR) 2021 ) introduces key topics from artificial intelligence algorithms and programming organization and explains how they contribute to autonomous capabilities. The book is primarily intended for researchers, students, and engineers who wish to use the applications of artificial intelligence to solve concrete problems. We hope that companies and technology developers also find it interesting to be used in industry.

This book of Advances in Deep Learning, Artificial Intelligence and Robotics (proceedings of ICDLAIR 2020) is intended to be used as a reference by students and researchers who collect scientific and technical contributions with respect to models, tools, technologies and applications in the field of modern artificial intelligence and robotics. Deep Learning, AI and robotics represent key ingredients for the 4th Industrial Revolution. Their extensive application is dramatically changing products and services, with a large impact on labour, economy and society at all. The research and reports of new technologies and applications in DL, AI and robotics like biometric recognition systems, medical diagnosis, industries, telecommunications, AI petri nets model-based diagnosis, gaming, stock trading, intelligent aerospace systems, robot control and web intelligence aim to bridge the gap between these non-coherent disciplines of knowledge and fosters unified development in next-generation computational models for machine intelligence.