Biological processes such as Cellular Respiration have an intricate structure that defines the ordering amongst different steps and the participants in each step. A person who understands the process is expected to be able to reason with how the process is affected if one or more steps is interrupted. In this paper, we analyze a family of questions about process interruption, and present reasoning patterns that an automated reasoner can use to answer them. Our reasoning patterns rely on the order of steps of the process and the participants of those steps. We suggest that this approach leads to more intuitive and simpler reasoning than an approach of based on theory of intentions 9,10, or an approach that relies on qualitative simulation 8.
%0 Conference Paper
%1 chaudhri2012process
%A Chaudhri, Vinay K.
%A Heymans, Stijn
%A Yorke-Smith, Neil
%B Second Workshop on Deep Knowledge Representation Challenge
%C Playa Vista, CA, USA
%D 2012
%K 2012 myown refereedpub
%T Process Interruption Reasoning
%U http://stijnheymans.net/pubs/dkrc2012.pdf
%X Biological processes such as Cellular Respiration have an intricate structure that defines the ordering amongst different steps and the participants in each step. A person who understands the process is expected to be able to reason with how the process is affected if one or more steps is interrupted. In this paper, we analyze a family of questions about process interruption, and present reasoning patterns that an automated reasoner can use to answer them. Our reasoning patterns rely on the order of steps of the process and the participants of those steps. We suggest that this approach leads to more intuitive and simpler reasoning than an approach of based on theory of intentions 9,10, or an approach that relies on qualitative simulation 8.
@inproceedings{chaudhri2012process,
abstract = {Biological processes such as Cellular Respiration have an intricate structure that defines the ordering amongst different steps and the participants in each step. A person who understands the process is expected to be able to reason with how the process is affected if one or more steps is interrupted. In this paper, we analyze a family of questions about process interruption, and present reasoning patterns that an automated reasoner can use to answer them. Our reasoning patterns rely on the order of steps of the process and the participants of those steps. We suggest that this approach leads to more intuitive and simpler reasoning than an approach of based on theory of intentions [9,10], or an approach that relies on qualitative simulation [8].},
added-at = {2012-07-20T21:34:50.000+0200},
address = {Playa Vista, CA, USA},
author = {Chaudhri, Vinay K. and Heymans, Stijn and Yorke-Smith, Neil},
biburl = {https://www.bibsonomy.org/bibtex/2c72f4e36ff25bab0ccaa98b4e6831324/stijn.heymans},
booktitle = {Second Workshop on Deep Knowledge Representation Challenge},
interhash = {1d43447fff830cc0b869fb1af697ea48},
intrahash = {c72f4e36ff25bab0ccaa98b4e6831324},
keywords = {2012 myown refereedpub},
month = {July},
timestamp = {2012-07-20T21:36:30.000+0200},
title = {Process Interruption Reasoning},
url = {http://stijnheymans.net/pubs/dkrc2012.pdf},
year = 2012
}