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Understanding Planning Tasks - Domain Complexity and Heuristic Decomposition (Paperback, 2008 ed.): Malte Helmert Understanding Planning Tasks - Domain Complexity and Heuristic Decomposition (Paperback, 2008 ed.)
Malte Helmert
R1,539 Discovery Miles 15 390 Ships in 10 - 15 working days

Action planning has always played a central role in Artificial Intelligence. Given a description of the current situation, a description of possible actions and a description of the goals to be achieved, the task is to identify a sequence of actions, i.e., a plan that transforms the current situation into one that satisfies the goal description.

This monograph is a revised version of Malte Helmert's doctoral thesis, Solving Planning Tasks in Theory and Practice, written under the supervision of Professor Bernhard Nebel as thesis advisor at Albert-Ludwigs-Universitat Freiburg, Germany, in 2006. The book contains an exhaustive analysis of the computational complexity of the benchmark problems that have been used in the past decade, namely the standard benchmark domains of the International Planning Competitions (IPC). At the same time, it contributes to the practice of solving planning tasks by presenting a powerful new approach to heuristic planning. The author also provides an in-depth analysis of so-called routing and transportation problems.

All in all, this book will contribute significantly to advancing the state of the art in automatic planning. "

KI 2016: Advances in Artificial Intelligence - 39th Annual German Conference on AI, Klagenfurt, Austria, September 26-30, 2016,... KI 2016: Advances in Artificial Intelligence - 39th Annual German Conference on AI, Klagenfurt, Austria, September 26-30, 2016, Proceedings (Paperback, 1st ed. 2016)
Gerhard Friedrich, Malte Helmert, Franz Wotawa
R2,464 Discovery Miles 24 640 Ships in 10 - 15 working days

This book constitutes the refereed proceedings of the 39th Annual German Conference on Artificial Intelligence, KI 2016, in conjunction with the OEsterreichische Gesellschaft fur Artificial Intelligence, OEGAI, held in Klagenfurt, Austria, in September 2016. The 8 revised full technical papers presented together with 12 technical communications, and 16 extended abstracts were carefully reviewed and selected from 44 submissions. The conference provides the opportunity to present a wider range of results and ideas that are of interest to the KI audience, including reports about recent own publications, position papers, and previews of ongoing work.

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