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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.
Sommario
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.
