Artificial Intelligence

Artificial Intelligence: Transcending Traditional Paradigms is a significant new introductory text for undergraduate and graduate course use. It introduces students and professionals to the state-of-the-art development of Artificial Intelligence techniques to develop smart real-world solutions. As an active researcher, the author presents the material authoritatively and with insights that reflect a modern, firsthand understanding of the field.

Artificial intelligence is a science still in its infancy, and that makes it special. It s not like more established fields, and the author has tried in writing this textbook to honour this characteristic and the ways it makes AI unique.

Part 1: Foundations of artificial intelligence. - The genesis of artificial intelligence: Origins and evaluation. - The dawn of AI: Early innovations and discoveries. - Part 2: The learning revolution: Data-driven intelligence. - Soft computing paradigms: Bridging precision and flexibility. - Machine learning: Building intelligence from patterns. - Deep learning: The fabric of representation. - Reinforcement learning: Shaping behaviour through rewards. - Part 3: AI Odyssey: Exploring language and intelligent agents. - Journey through language: Models and prompt engineering. - Autonomous decision maker: AI agents. - Part 4: Expanding the frontiers of AI. - The best of both Worlds: Neuro-symbolic AI. - Mimicking the mind: Evolution of cognitive AI. - Robots with a sense of self: Exploring embodied intelligence. - Part 5: Building advanced and responsible AI. - Blueprint for intelligence: Building robust AI systems. - Never stop learning: The principles of continual learning. - Opening the black box: The role of explainability in AI. - Part 6: Conclusion and future outlook. - Epilogue: AI at the threshold.