Artificial intelligence (AI) is a complicated science that combines philosophy, cognitive psychology, neuroscience, mathematics and logic (logicism), economics, computer science, computability, and software. Meanwhile, robotics is an engineering field that compliments AI. There can be situations where AI can function without a robot (e.g., Turing Test) and robotics without AI (e.g., teleoperation), but in many cases, each technology requires each other to exhibit a complete system: having "smart" robots and AI being able to control its interactions (i.e., effectors) with its environment. This book provides a complete history of computing, AI, and robotics from its early development to state-of-the-art technology, providing a roadmap of these complicated and constantly evolving subjects.

Divided into two volumes covering the progress of symbolic logic and the explosion in learning/deep learning in natural language and perception, this second volume goes more in-depth into the history of artificial intelligence, starting with key people and important events that bring us to the present day.

Key Features:

Builds on the insights provided in volume 1 to look into the future of AI and robotics. Provides a holistic view of AI, and touches on all the misconceptions and tangents to the technologies through taking a systematic approach. Provides a glossary of terms, list of notable people, and extensive references. Provides the interconnections and history of the progress of technology for over 100 years as both the hardware (Moore's Law, GPUs) and software, i.e., generative AI, has advanced.

Intended as a complete reference, this book is useful to undergraduate and postgraduate students of computing, as well as the general reader. It can also be used as a textbook by course convenors. If you only had one book on AI and robotics, this set would be the first reference to acquire and learn about the theory and practice.