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Please use this identifier to cite or link to this item:
http://hdl.handle.net/2451/14374
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| Title: | DESIGNING OBJECT-ORIENTED REPRESENTATIONS FOR REASONING FROM FIRST-PRINCIPLES |
| Authors: | Benaroch, Michel |
| Issue Date: | Jul-1991 |
| Publisher: | Stern School of Business, New York University |
| Series/Report no.: | IS-91-19 |
| Abstract: | Modeling expert knowledge using "situation-action" rules is
not always feasible in knowledge intensive domains involving volatile
knowledge (e.g., trading). The explosive search space involved in such
domains and its dynamic nature make it extremely difficult to setup a
rule base and keep it accurate. An alternative approach suggests that in
some domains many of the rules expert use can be derived by reasoning
from "first-principles". That approach entails modeling
experts' deep knowledge, and emulating reasoning processes with deep
knowledge that allow experts to derive many of the rules they use and
justify them. This paper discusses the design and implementation of an
object-oriented representation for the deep knowledge traders utilize in
a business domain called hedging, which is knowledge intensive and
involves volatile knowledge. It illustrates how deep knowledge modeled
using that representation is used to support reasoning from
first-principles. The paper also analyzes features of that
representation that we have found to be extremely beneficial in the
development of a knowledge-based system called INTELLIGENT-HEDGER. Based
on our experience we feel that, with minor modifications, this
representation can be used in other managerial domains involving
financial reasoning. |
| URI: | http://hdl.handle.net/2451/14374 |
| Appears in Collections: | IOMS: Information Systems Working Papers
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