Correcting Object-Related Misconceptions: How Should The System Respond?

Correcting Object-Related Misconceptions: How Should The System Respond? t Kathleen F. McCoy Department of Computer & Inft~rmation Science University of Pennsylvania Philadelphia, PA 19104 Abstract Tills paper describes a computational method for correcting users' miseonceptioas concerning the objects modelled by a compute," s.ystem. The method involves classifying object-related misc,mce|,tions according to the knowledge-base feature involved in the incorrect information. For each resulting class sub-types are identified, :.:cording to the structure of the knowledge base, which indicate wh:LI i.formativn may be supporting the misconception and therefore what information to include in the response. Such a characteriza*i,,n, along with a model of what the user knows, enables the syst.cm to reas,m in a domain-independent way about how best to c~rrv,'t [he user. 1. Introduction A meier ar,.a of Al research has been the development of "expert sys.tcms" - systems which are able to answer user's que:~titms concerning a particular domain. Studies identifying desirabl,, iutora,'tive capabilities for such systems [Pollack et al. 82] have ft,und that. it is not sufficient simply to allow the user to ,~k a question and Itavo the system answ~.r it. Users often want to question the system's rea-~oning,to make sure certain constraints have been taken into consideration, anti so on. Thus we must strive to provide expert systems with the ability to interact with the user in the kind of cooperative di:LIogues that we see between two bullish ctmversational partners. Allowing .,uch interactions between the system and a user raises difficulties for a Natural-Language system. Since the user is interacting with a system a.s s/he would with a human export, s/he will nizam likely exp-ct the system to b(have as a human expert. Among other things, the n:.er will expect the systenl to be adhering to the cooperative principles of conversation [Grice 7,5, .loshi 821. If these principte~ are not followed by the system, the user is bkeiy to become confu~ed. In this paper I.focus on one a,;pect of the cooperative behavior found between two conversat, ional partners: responding to recognized differences in the beliefs of the two participants. Often when two people interact, ouc reveals-a belief or assumption that is incompatible with the b~*liefs held by the other. Failure to correct this disparity may not only implicitly confirm the disparate bcli,'f, but may even make it impos~;ibie to complete tile ongoing task. Imagine the following excilange: U. Give ll|e the ItUI.L NO of all Destroyers whose MAST_IIEIGIIT is above 190. E. All Destrt,yers that I know al)out |lave a MAbT_HEIGllT between 85 and 90. Were you thinking of the Aircraft-Carriers? in this example, the user (U) ha.s apparently ctmfused a Destroyer with an Aircraft-Carrier. This confusion has caused her to attribute a property value to Destroyers that they do not have. In this case a correct a/tswer by the expert (E} of *none" is likely to confuse U'. In order to continue the conver.-ation with a minimal amount of eoafu.~ion, the user's incorrect belief must first be addressed. My primary interest is in what an expert system, …

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