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Artificial Intelligence: A Modern Approach (AIMA) is a university textbook on artificial intelligence, written by Stuart J. Russell and Peter Norvig. It was first published in 1995 and the third edition of the book was released 11 December 2009. It is used in over 1100 universities worldwide and has been called "the most popular artificial intelligence textbook in the world". It is considered the standard text in the field of artificial intelligence. The book is intended for an undergraduate audience but can also be used for graduate-level studies with the suggestion of adding some of the primary sources listed in the extensive bibliography.

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The Artificial Intelligence Robot STEM Kit lets you build an intelligent, six-legged, app-enabled robot that uses machine learning to react to your gestures and sounds. Download the free app for your mobile device to record the voice commands and gestures you'll use to make it walk, turn and stop. The more data you collect, the better the AI will learn from it. App compatible with iPhone/iPad (iOS 11.0 or later) and Galaxy/Android (OS 8.0 or later). Ages 10+.

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Artificial Intelligence DJ Haus - LP 800071004873

Intelligent agents are employed as the central characters in this new introductory text. Beginning with elementary reactive agents, Nilsson gradually increases their cognitive horsepower to illustrate the most important and lasting ideas in AI. Neural networks, genetic programming, computer vision, heuristic search, knowledge representation and reasoning, Bayes networks, planning, and language understanding are each revealed through the growing capabilities of these agents. The book provides a refreshing and motivating new synthesis of the field by one of AI's master expositors and leading researchers. Artificial Intelligence: A New Synthesis takes the reader on a complete tour of this intriguing new world of AI.An evolutionary approach provides a unifying theme Thorough coverage of important AI ideas, old and newFrequent use of examples and illustrative diagramsExtensive coverage of machine learning methods throughout the textCitations to over 500 referencesComprehensive index

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Artificial Intelligence and Scientific Method examines the remarkable advances made in the field of AI over the past twenty years, discussing their profound implications for philosophy. Taking a clear, non-technical approach, Donald Gillies focuses on two key topics within AI: machine learning in the Turing tradition and the development of logic programming and its connection with non-monotonic logic. Demonstrating how current views on scientific method are challenged by this recent research, he goes on to suggest a new framework for the study of logic. He draws on work by such seminal thinkers as Bacon, Gödel, Popper, Penrose, and Lucas to address the hotly contested question of whether computers might become intellectually superior to human beings. These topics will attract a wide readership from followers of advances in artificial intelligence, to students and scholars of the history and philosophy of science.

The history of robotics and artificial intelligence in many ways is also the history of humanity’s attempts to control such technologies. From the Golem of Prague to the military robots of modernity, the debate continues as to what degree of independence such entities should have and how to make sure that they do not turn on us, its inventors. Numerous recent advancements in all aspects of research, development and deployment of intelligent systems are well publicized but safety and security issues related to AI are rarely addressed. This book is proposed to mitigate this fundamental problem. It is comprised of chapters from leading AI Safety researchers addressing different aspects of the AI control problem as it relates to the development of safe and secure artificial intelligence. The book is the first edited volume dedicated to addressing challenges of constructing safe and secure advanced machine intelligence. The chapters vary in length and technical content from broad interest opinion essays to highly formalized algorithmic approaches to specific problems. All chapters are self-contained and could be read in any order or skipped without a loss of comprehension.

Book is in Used-VeryGood condition. Pages and cover are clean and intact. Used items may not include supplementary materials such as CDs or access codes. May show signs of minor shelf wear and contain very limited notes and highlighting. 2.07

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The long-anticipated revision of this best-selling book offers the most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence. Intelligent Agents. Solving Problems by Searching. Informed Search Methods. Game Playing. Agents that Reason Logically. First-order Logic. Building a Knowledge Base. Inference in First-Order Logic. Logical Reasoning Systems. Practical Planning. Planning and Acting. Uncertainty. Probabilistic Reasoning Systems. Making Simple Decisions. Making Complex Decisions. Learning from Observations. Learning with Neural Networks. Reinforcement Learning. Knowledge in Learning. Agents that Communicate. Practical Communication in English. Perception. Robotics. For those interested in artificial intelligence.

Each title in the highly acclaimed Opposing Viewpoints series explores a specific issue by placing expert opinions in a unique pro/con format; the viewpoints are selected from a wide range of highly respected and often hard-to-find publications.; ; "Each volume in the Opposing Viewpoints Series could serve as a model...not only providing access to a wide diversity of opinions, but also stimulating readers to do further research for group discussion and individual interest. Both shrill and moderate, th

Examines both theory and its practical applications. Includes discussions of the practical problems involved in their implementation. Textbook.

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Paperback. Artificial intelligence is creating huge opportunities for workplace learning and employee development. However, it can be difficult for L&D professionals to assess what difference AI can make in their organization and where it is best implemented. Artificial Intelligence for Learning is the practical guide L&D practitioners need to understand what AI is and how to use it to improve all aspects of learning in the workplace. It includes specific guidance on how AI can provide content curation and personalization to improve learner engagement, how it can be implemented to improve the efficiency of evaluation, assessment and reporting and how chatbots can provide learner support to a global workforce.Artificial Intelligence for Learning debunks the myths and cuts through the hype around AI allowing L&D practitioners to feel confident in their ability to critically assess where artificial intelligence can make a measurable difference and where it is worth investing in. There is also critical discussion of how AI is an aid to learning and development, not a replacement as well as how it can be used to boost the effectiveness of workplace learning, reduce drop off rates in online learning and improve ROI. With real-world examples from companies who have effectively implemented AI and seen the benefits as well as case studies from organizations including Netflix, British Airways and the NHS, this book is essential reading for all L&D practitioners needing to understand AI and what it means in practice. Critically assess the impact of artificial intelligence on the L&D function and understand how to use it to improve learning in the workplace. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.