
Techniques for reasoning about actions and change in the physical world are among the classic research topics in artificial intelligence, motivated by the needs of autonomous robots which must be able to anticipate future developments and analyze problems. This monograph presents a novel methodology for such reasoning. It is based on a systematic approach for identifying the exact range of applicability of a given logic, as opposed to traditional methods based on proposing new logic variants supported by episodical examples. For a number of previously proposed logics, as well as for some new ones, this work characterizes exactly the class of those reasoning tasks where the logic results in the intended set of conclusions, and the class were it does not. The book will be a necessary resource for researchers in knowledge representation, cognitive robotics, and intelligent control. It can also be recommended as a graduate-level text in these fields, especially in light of its emphasis on a strict and systematic methodology.
This work investigates the formal representation of knowledge regarding dynamical systems to improve how autonomous agents reason about actions and change. Erik Sandewall, a prominent researcher in artificial intelligence, provides a rigorous methodology for evaluating the applicability of various logics. By moving away from anecdotal examples, the author establishes a systematic framework to determine the precise conditions under which specific reasoning tasks yield intended conclusions.
What You Will Find
Experts recognize this monograph as a foundational text for researchers focused on knowledge representation and automated reasoning. Readers frequently note the high level of academic density and the systematic rigor applied to the study of dynamical systems.
Page Count:
352
Publication Date:
1995-02-09
Publisher:
Clarendon Press
ISBN-10:
0198538456
ISBN-13:
9780198538455
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