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Artificial Intelligence
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  • Cited by 82
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    This book has been cited by the following publications. This list is generated based on data provided by CrossRef.

    Sah, Arun Kumar Mohanty, Prases K. Kumar, Vikas and Chhotray, Animesh 2019. Computational Intelligence in Data Mining. Vol. 711, Issue. , p. 237.

    Arnatovich, Yauhen Leanidavich Wang, Lipo Ngo, Ngoc Minh and Soh, Charlie 2018. Mobolic: An automated approach to exercising mobile application GUIs using symbiosis of online testing technique and customated input generation. Software: Practice and Experience, Vol. 48, Issue. 5, p. 1107.

    Kim, Min-Sun 2018. Robot as the “mechanical other”: transcending karmic dilemma. AI & SOCIETY,

    Guraksin, Gur Emre 2018. Nature-Inspired Intelligent Techniques for Solving Biomedical Engineering Problems. p. 263.

    Gonsalves, Tad 2018. Encyclopedia of Information Science and Technology, Fourth Edition. p. 229.

    Krishnamurthy, Kamalanand and Ponnuswamy, Mannar Jawahar 2018. Nature-Inspired Intelligent Techniques for Solving Biomedical Engineering Problems. p. 27.

    Batarseh, Feras A. 2018. Encyclopedia of Big Data. p. 1.

    Lopes, Fernando and Coelho, Helder 2018. Electricity Markets with Increasing Levels of Renewable Generation: Structure, Operation, Agent-based Simulation, and Emerging Designs. Vol. 144, Issue. , p. 49.

    Boger, Jennifer Young, Victoria Hooey, Jesse Jiancaro, Tizneem and Mihailidis, Alex 2018. Zero Effort Technologies: Considerations, Challenges, and Use in Health, Wellness, and Rehabilitation,Second Edition. Synthesis Lectures on Assistive, Rehabilitative, and Health-Preserving Technologies, Vol. 8, Issue. 1, p. i.

    Havlík, Vladimír 2018. The naturalness of artificial intelligence from the evolutionary perspective. AI & SOCIETY,

    Pedersen, Tore Johansen, Christian and Jøsang, Audun 2018. Behavioural Computer Science: an agenda for combining modelling of human and system behaviours. Human-centric Computing and Information Sciences, Vol. 8, Issue. 1,

    Nalepa, Grzegorz J. 2018. Modeling with Rules Using Semantic Knowledge Engineering. Vol. 130, Issue. , p. 155.

    Lawniczak, Anna T. and Yu, Fei 2017. Decisions and success of heterogeneous population of agents in learning to cross a highway. p. 1.

    Capeluto, Guedi and Ochoa, Carlos Ernesto 2017. Intelligent Envelopes for High-Performance Buildings. p. 1.

    Zhang, Wuyang Chen, Jiachen Zhang, Yanyong and Raychaudhuri, Dipankar 2017. Towards efficient edge cloud augmentation for virtual reality MMOGs. p. 1.

    Faber, Marco Mertens, Alexander and Schlick, Christopher M. 2017. Cognition-enhanced assembly sequence planning for ergonomic and productive human–robot collaboration in self-optimizing assembly cells. Production Engineering, Vol. 11, Issue. 2, p. 145.

    Panghal, Deepak Kumar, Shailendra and Hussein, Hussein M. A. 2017. AI Applications in Sheet Metal Forming. p. 245.

    Mohanty, Prases K. Sah, Arun Kumar Kumar, Vikas and Kundu, Shubhasri 2017. Application of Deep Q-Learning for Wheel Mobile Robot Navigation. p. 88.

    Tampuu, Ardi Matiisen, Tambet Kodelja, Dorian Kuzovkin, Ilya Korjus, Kristjan Aru, Juhan Aru, Jaan Vicente, Raul and Xia, Cheng-Yi 2017. Multiagent cooperation and competition with deep reinforcement learning. PLOS ONE, Vol. 12, Issue. 4, p. e0172395.

    Luo, Jieting Meyer, John-Jules and Knobbout, Max 2017. Autonomous Agents and Multiagent Systems. Vol. 10642, Issue. , p. 203.


Book description

Recent decades have witnessed the emergence of artificial intelligence as a serious science and engineering discipline. This textbook, aimed at junior to senior undergraduate students and first-year graduate students, presents artificial intelligence (AI) using a coherent framework to study the design of intelligent computational agents. By showing how basic approaches fit into a multidimensional design space, readers can learn the fundamentals without losing sight of the bigger picture. The book balances theory and experiment, showing how to link them intimately together, and develops the science of AI together with its engineering applications. Although structured as a textbook, the book's straightforward, self-contained style will also appeal to a wide audience of professionals, researchers, and independent learners. AI is a rapidly developing field: this book encapsulates the latest results without being exhaustive and encyclopedic. The text is supported by an online learning environment, AIspace,, so that students can experiment with the main AI algorithms plus problems, animations, lecture slides, and a knowledge representation system, AIlog, for experimentation and problem solving.


'This book, by two of the foremost researchers in Artificial Intelligence, marks the transition of the field from a miscellaneous assortment of unrelated techniques to a genuine scientific discipline. It presents the fundamental concepts of AI in a coherent structure, which shows how different techniques are related and complementary. The book is written in a clear and engaging manner, which makes it suitable both for the serious student and for the intellectually curious layperson.'

Robert Kowalski - Imperial College London

'The clarity of this book is amazing! Material in each chapter is a perfect blend of accessible stuff for beginners, theory and challenges for advanced students, and reference materials for experts, organized into sections so you can split off the right bits for your students. Its like having three textbooks in one! Definitely the must-have textbook on AI for the 21st century. I know mine will be within reach for years to come.'

Jesse Hoey - University of Dundee

'This book fills a real gap in the AI literature. It is accessible for advanced undergraduate students, without compromising technical rigor. It is concise, but still gives a modern presentation of all major areas of AI. It is an eminently useful textbook for introductory courses to AI. Poole and Mackworth have made a valiant effort to impose some order on the wide and heterogeneous field of Artificial Intelligence. In this order, all of AI is placed in a design space for intelligent agents defined by dimensions of complexity.'

Manfred Jaeger - Aalborg University

'This text is a modern and coherent introduction to the field of Artificial Intelligence that uses rational computational agents and logic as unifying threads in this vast field. Many fully worked out examples, a good collection of paper-and-pencil exercises at various levels of difficulty, programming assignments based on the custom-designed declarative AILog language, and well-integrated online support through the AISpace applets complement the presentation. If you plan to teach a course in Artificial Intelligence at the upper-division undergraduate level or beyond, you must give serious consideration to this thoroughly enjoyable book.'

Marco Valtorta - University of South Carolina

'The book covers a great variety of topics and every matter is presented with the best care for the understanding of the reader. The book is addressed to anyone who is interested in designing a smart agent: the explanations are very generous, but without being exaggerated … reading the text, the excitement of the authors about AI becomes obvious and even contagious. Even specialists in this field will find precious information and delightful interpretations. Without a shred of doubt, this textbook will very soon become basic material for the courses of AI at universities worldwide.'

Source: Zentralblatt MATH

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