Dissertation Abstract
Abductive Inference In Computation
by
Gerald Barkley Berdan
Degree: M.S.
Year: 1997
Pages: 00094
Institution:
Advisor: Roger Cavallo
Source: MAI, 36, no. 02, (1997): 0560
Abduction, a form of ampliative reasoning that is
usually defined as inference to the best explanation, was originally described
by Charles Sanders Peirce at the end of the nineteenth century, and is only
lately being implemented in computer systems. Peirce laid out a bare framework
for abduction and left its complex details undefined as an intrinsic part of
human psychology. Abduction's implementation in a mechanical system requires that
additional details be fully considered, generating far more complexity than
Peirce could have imagined. Efforts towards complex implementations are still
in infancy.
In
this paper I develop the general requirements for implementing abductive
inference including knowledge representation and implementation algorithms. I
investigate the issues that must be considered in this implementation, which
include the criteria for both hypothesis generation and selection. Since
abduction is only productive within complex systems, it therefore finds an
optimal implementation in object-oriented software.
SUBJECT(S)
Descriptor: COMPUTER SCIENCE
Accession
No: AAG1387503
Provider: OCLC
Database: Dissertations