Deriving Causal Explanation from Qualitative Model Reasoning
This paper discusses a qualitative simulator QRiOM
that uses Qualitative Reasoning (QR) technique, and a process-based
ontology to model, simulate and explain the behaviour of selected
organic reactions. Learning organic reactions requires the application
of domain knowledge at intuitive level, which is difficult to be
programmed using traditional approach. The main objective of
QRiOM is to help learners gain a better understanding of the
fundamental organic reaction concepts, and to improve their
conceptual comprehension on the subject by analyzing the multiple
forms of explanation generated by the software. This paper focuses
on the generation of explanation based on causal theories to explicate
various phenomena in the chemistry subject. QRiOM has been tested
with three classes problems related to organic chemistry, with
encouraging results. This paper also presents the results of
preliminary evaluation of QRiOM that reveal its explanation
capability and usefulness.
[1] K. Forbus, "Qualitative Process Theory," Artificial Intelligence, 24 85-
125, 1984.
[2] B. Bredeweg, and K. Forbus, "Qualitative Modelling in Education," AI
Magazine 24(4), 35-46, 2003.
[3] P.S.B.A. Salles, H. Pain, and R.I. Muetzelfeldt, "Qualitative ecological
models for tutoring systems: a comparative study," AAAI Technical
Report WS-96-01, 1996.
[4] Y.C. Alicia Tang, and S.M.F.D. Syed Mustapha, "Representing SN1
Reaction Mechanism Using the Qualitative Process Theory," in Proc.
20th Int. Workshop on Qualitative Reasoning, eds. C. Bailey-Kellogg
and B. Kuipers, Hanover, USA, 2006, pp. 137-147.
[5] Y.C. Alicia Tang, S.M.F.D. Syed Mustapha, R. Abdullah, S.M. Zain,
and N. A. Rahman, "Towards Automating QPT Model Construction for
Reaction Mechanisms Simulation", in Proceedings of the 21st
International Workshop on Qualitative Reasoning, Aberystwyth, United
Kingdom, 2007.
[6] Y.C. Alicia Tang, S.M. Zain, N. Abdul Rahman, and R. Abdullah, "An
ontology-based reasoning framework for reaction mechanisms
simulation," Lecture Notes in Artificial Intelligence (LNAI) 4798,
Springer-Verlag Berlin Heidelberg, 2007, pp. 18-29.
[7] Y. C. Alicia Tang, R. Abdullah, S.M. Zain, and N.A. Rahman.
"Generating Qualitative Causal Graph using Modeling Constructs of
Qualitative Process Theory for Explaining Organic Chemistry
Reactions", International Journal of Information Technology 5:1 2009,
pp. 1-11, World Academy of Science, Engineering and Technology.
[1] K. Forbus, "Qualitative Process Theory," Artificial Intelligence, 24 85-
125, 1984.
[2] B. Bredeweg, and K. Forbus, "Qualitative Modelling in Education," AI
Magazine 24(4), 35-46, 2003.
[3] P.S.B.A. Salles, H. Pain, and R.I. Muetzelfeldt, "Qualitative ecological
models for tutoring systems: a comparative study," AAAI Technical
Report WS-96-01, 1996.
[4] Y.C. Alicia Tang, and S.M.F.D. Syed Mustapha, "Representing SN1
Reaction Mechanism Using the Qualitative Process Theory," in Proc.
20th Int. Workshop on Qualitative Reasoning, eds. C. Bailey-Kellogg
and B. Kuipers, Hanover, USA, 2006, pp. 137-147.
[5] Y.C. Alicia Tang, S.M.F.D. Syed Mustapha, R. Abdullah, S.M. Zain,
and N. A. Rahman, "Towards Automating QPT Model Construction for
Reaction Mechanisms Simulation", in Proceedings of the 21st
International Workshop on Qualitative Reasoning, Aberystwyth, United
Kingdom, 2007.
[6] Y.C. Alicia Tang, S.M. Zain, N. Abdul Rahman, and R. Abdullah, "An
ontology-based reasoning framework for reaction mechanisms
simulation," Lecture Notes in Artificial Intelligence (LNAI) 4798,
Springer-Verlag Berlin Heidelberg, 2007, pp. 18-29.
[7] Y. C. Alicia Tang, R. Abdullah, S.M. Zain, and N.A. Rahman.
"Generating Qualitative Causal Graph using Modeling Constructs of
Qualitative Process Theory for Explaining Organic Chemistry
Reactions", International Journal of Information Technology 5:1 2009,
pp. 1-11, World Academy of Science, Engineering and Technology.
@article{"International Journal of Chemical, Materials and Biomolecular Sciences:50348", author = "Alicia Y. C. Tang and Sharifuddin M. Zain and Noorsaadah A. Rahman and Rukaini Abdullah", title = "Deriving Causal Explanation from Qualitative Model Reasoning", abstract = "This paper discusses a qualitative simulator QRiOM
that uses Qualitative Reasoning (QR) technique, and a process-based
ontology to model, simulate and explain the behaviour of selected
organic reactions. Learning organic reactions requires the application
of domain knowledge at intuitive level, which is difficult to be
programmed using traditional approach. The main objective of
QRiOM is to help learners gain a better understanding of the
fundamental organic reaction concepts, and to improve their
conceptual comprehension on the subject by analyzing the multiple
forms of explanation generated by the software. This paper focuses
on the generation of explanation based on causal theories to explicate
various phenomena in the chemistry subject. QRiOM has been tested
with three classes problems related to organic chemistry, with
encouraging results. This paper also presents the results of
preliminary evaluation of QRiOM that reveal its explanation
capability and usefulness.", keywords = "Artificial intelligence, explanation, ontology, organicreactions, qualitative reasoning, QPT.", volume = "3", number = "11", pages = "603-8", }