Constructing and revising commonsense science explanations: A metareasoning approach

Scott E. Friedman*, Kenneth D Forbus, Bruce L Sherin

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations


Reasoning with commonsense science knowledge is an important challenge for Artificial Intelligence. This paper presents a system that revises its knowledge in a commonsense science domain by constructing and evaluating explanations. Domain knowledge is represented using qualitative model fragments, which are used to explain phenomena via model formulation. Metareasoning is used to (1) score competing explanations numerically along several dimensions and (2) evaluate preferred explanations for global consistency. Inconsistencies cause the system to favor alternative explanations and thereby change its beliefs. We simulate the belief changes of several students during clinical interviews about how the seasons change. We show that qualitative models accurately represent student knowledge and that our system produces and revises a sequence of explanations similar those of the students.

Original languageEnglish (US)
Title of host publicationAdvances in Cognitive Systems - Papers from the AAAI Fall Symposium, Technical Report
Number of pages8
StatePublished - Dec 1 2011
Event2011 AAAI Fall Symposium - Arlington, VA, United States
Duration: Nov 4 2011Nov 6 2011


Other2011 AAAI Fall Symposium
CountryUnited States
CityArlington, VA

ASJC Scopus subject areas

  • Engineering(all)

Fingerprint Dive into the research topics of 'Constructing and revising commonsense science explanations: A metareasoning approach'. Together they form a unique fingerprint.

Cite this