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Generating Explanations for Goal‐Based Decision Making *
Author(s) -
Slade Stephen
Publication year - 1992
Publication title -
decision sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.238
H-Index - 108
eISSN - 1540-5915
pISSN - 0011-7315
DOI - 10.1111/j.1540-5915.1992.tb00458.x
Subject(s) - voting , computer science , business decision mapping , decision engineering , management science , investment decisions , decision support system , investment (military) , domain (mathematical analysis) , knowledge management , operations research , artificial intelligence , economics , political science , microeconomics , behavioral economics , engineering , politics , law , mathematical analysis , mathematics
As information systems make the transition from decision support to decision making, there will be a concomitant need for the programs to explain or justify their actions. Without such explanations, humans will not readily cede authority to a machine. This paper describes an automated decision‐making program, VOTE, which generates natural language explanations for its decisions in both English and French. The program domain is Congressional roll call voting. VOTE simulates voting decisions of specific members of the United States House of Representatives on given bills. VOTE's natural language generation facility is also used by the underlying databases to interpret the knowledge representations. These underlying knowledge representations are described and applications of this decision making model to the general business domains of strategic planning, investment, and marketing are suggested.