Dissertation Abstract





Abductive Inference In Computation


Gerald Barkley Berdan


Degree:           M.S.

Year:             1997

Pages:            00094

Institution:      State University Of New York Institute Of Technology At Utica-Rome; 1026

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.



Descriptor:       COMPUTER SCIENCE

Accession No:     AAG1387503

Provider:        OCLC

Database:         Dissertations