Abstract
The performance of all reasoning systems crucially depends on problem representation: the same problem may be easy or difficult, depending on the way we describe it. Researchers in psychology, cognitive science, and artificial intelligence have accumulated much evidence on the importance of appropriate representations for human problem solvers and AI systems.
Could you restate the problem? Could you restate it still differently?
— George Polya [1957], How to Solve It.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2002 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Fink, E. (2002). Motivation. In: Changes of Problem Representation. Studies in Fuzziness and Soft Computing, vol 110. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-1774-4_1
Download citation
DOI: https://doi.org/10.1007/978-3-7908-1774-4_1
Publisher Name: Physica, Heidelberg
Print ISBN: 978-3-7908-2518-3
Online ISBN: 978-3-7908-1774-4
eBook Packages: Springer Book Archive