tailieunhanh - Báo cáo khoa học: "Preventing False Inferences "

Introduction In cooperative man-machine interaction, it is taken as necessary that a system truthfully and informatively respond to a user's question. It is not, however, sufficient. In particular, if the system has reason to believe that its planned response nfight lead the user to draw an inference that it knows to be false, then it must block it by nmdifying or adding to its response. The problem is that a system neither can nor should explore all eonchtsions a user might possibly draw: its reasoning must be constrained in some systematic and well-motivated way. Such cooperative behavior was. | Preventing False Inferences1 Aravind Joshi and Donnie Webber Department of Computer and Information Science Moore School D2 University of Pennsylvania Philadelphia PA 19104 ABSTRACT I Introduction In cooperative man-machine interaction it is taken as necessary that a system truthfully and informatively respond to a user s question. It is not however sufficient. In particular if the system has reason to believe that its planned response might lead the user to draw an inference that it knows to be false then it must block it by modifying or adding to its response. The problem is that a system neither can nor should explore all conclusions a user might possibly draw its reasoning must be constrained in some systematic and well-motivated way. Such cooperative behavior was investigated in 5 in which a modification of Grice s Maxim of Quality is proposed Grice s Maxim of Quality - Do not say what you believe to be false or for which you lack adequate evidence. Joshi s Revised Maxim of Quality - If you the speaker plan to say anything which may imply for the hearer something that you believe to be false then provide further information to block it. This behavior was studied in the context of interpreting certain definite noun phrases. In this paper we investigate this revised principle as applied to question answering. In particular the goals of the research described here are to 1. characterize tractable cases in which the system as respondent R can anticipate the possibility of the user questionér Q drawing false conclusions from its response and can hence alter or expand its response so as to prevent it happening 2. develop a formal method for computing the projected inferences that Q may draw from a particular response identifying those 1This work is partially supported by NSF Grants MCS 81-07290 MCS 83-05221 and 1ST 83-11100. 2 . At present visiting the Department of Computer and Information Science University of Pennsylvania Philadelphia PA 19104. Ralph M. .

• Báo cáo khoa học
• Preventing False Inferences
• Ralph M
• Weischedel
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