The study of artificial intelligence (AI) is indeed a strange pursuit. Unlike most other disciplines, few AI researchers even agree on a mutually acceptable definition of their chosen field of study. Some see AI as a sub field of computer science, others see AI as a computationally oriented branch of psychology or linguistics, while still others see it as a bag of tricks to be applied to an entire spectrum of diverse domains. This lack of unified purpose among the AI community makes this a very exciting time for AI research: new and diverse projects are springing up literally every day. As one might imagine, however, this diversity also leads to genuine difficulties in assessing the significance and validity of AI research. These difficulties are an indication that AI has not yet matured as a science: it is still at the point where people are attempting to lay down (hopefully sound) foundations. Ritchie and Hanna [1] posit the following categorization as an aid in assessing the validity of an AI research endeavor: (1) The project could introduce, in outline, a novel (or partly novel) idea or set of ideas. (2) The project could elaborate the details of some approach. Starting with the kind of idea in (1), the research could criticize it or fill in further details (3) The project could be an AI experiment, where a theory as in (1) and (2) is applied to some domain. Such experiments are usually computer programs that implement a particular theory.

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Authors and Affiliations

Cornell University, USA

Alberto Maria Segre

Bibliographic Information

Book Title: Machine Learning of Robot Assembly Plans
Authors: Alberto Maria Segre
Series Title: The Springer International Series in Engineering and Computer Science
DOI: https://doi.org/10.1007/978-1-4613-1691-6
Publisher: Springer New York, NY
eBook Packages: Springer Book Archive
Copyright Information: Kluwer Academic Publishers 1988
Hardcover ISBN: 978-0-89838-269-3Published: 30 April 1988
Softcover ISBN: 978-1-4612-8954-8Published: 05 October 2011
eBook ISBN: 978-1-4613-1691-6Published: 06 December 2012
Series ISSN: 0893-3405
Edition Number: 1
Number of Pages: XVIII, 234
Topics: Artificial Intelligence

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Table of contents (8 chapters)

Front Matter

Back Matter

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