There are many problems with the simplification of elementary functions, particularly over the complex plane. Systems tend to make major errors, or not to simplify enough. In this paper we outline the "unwinding number" approach to such problems, and show how it can be used to prevent errors and to systematise such simplification, even though we have not yet reduced the simplification process to a complete algorithm. The unsolved problems axe probably more amenable to the techniques of artificial intelligence and theorem proving than the original problem of complex-variable analysis.
|Title of host publication||Artificial Intelligence and Symbolic Computation|
|Subtitle of host publication||Revised Papers|
|Editors||J. A. Campbell, E. Roanes-Lozano|
|Place of Publication||Berlin, Germany|
|Number of pages||12|
|Publication status||Published - 2001|
|Event||International Conference Artificial Intelligence and Symbolic Computation (AISC), 2000 - Madrid, Spain|
Duration: 17 Jul 2000 → 19 Jul 2000
|Name||Lecture Notes in Artificial Intelligence|
|Conference||International Conference Artificial Intelligence and Symbolic Computation (AISC), 2000|
|Period||17/07/00 → 19/07/00|
Corless, R. M., Davenport, J. H., Jeffrey, D. J., Litt, G., & Watt, S. M. (2001). Reasoning about the elementary functions of complex analysis. In J. A. Campbell, & E. Roanes-Lozano (Eds.), Artificial Intelligence and Symbolic Computation: Revised Papers (pp. 115-126). (Lecture Notes in Artificial Intelligence; Vol. 1930). Springer.