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  • Coming soon
Publisher:
Cambridge University Press
Expected online publication date:
June 2025
Print publication year:
2025
Online ISBN:
9781009579346

Book description

AI's next big challenge is to master the cognitive abilities needed by intelligent agents that perform actions. Such agents may be physical devices such as robots, or they may act in simulated or virtual environments through graphic animation or electronic web transactions. This book is about integrating and automating these essential cognitive abilities: planning what actions to undertake and under what conditions, acting (choosing what steps to execute, deciding how and when to execute them, monitoring their execution, and reacting to events), and learning about ways to act and plan. This comprehensive, coherent synthesis covers a range of state-of-the-art approaches and models –deterministic, probabilistic (including MDP and reinforcement learning), hierarchical, nondeterministic, temporal, spatial, and LLMs –and applications in robotics. The insights it provides into important techniques and research challenges will make it invaluable to researchers and practitioners in AI, robotics, cognitive science, and autonomous and interactive systems.

Reviews

‘Every serious student of AI will benefit from reading this comprehensive text on some of the most important problems and methods underlying intelligent behavior, written by three world-leading experts.’

Stuart Russell - University of California, Berkeley

‘The book provides a comprehensive, advanced, and up-to-date introduction to the area of intelligent behaviour in AI concerned with acting, planning, and learning. It is also an original and ambitious work of synthesis that integrates classical and hierarchical planning, reinforcement learning, and robotics. An essential textbook and a key reference for anyone working in the field.’

Hector Geffner - RWTH Aachen University, Germany

‘After focusing on automated planning in their first book and its integration with acting in the second book, Malik Ghallab, Dana Nau, and Paolo Traverso close the loop by adding the last missing component, learning. With more than 600 pages of text and more than 1200 references, this massive effort is a must-read for anyone who builds autonomous agents that plan their actions and improve their behavior via learning. It is not only an excellent textbook, but it also serves as a reference book for researchers.’

Roman Barták - Charles University, Czech Republic

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