Duration Consistency Filtering for Qualitative Simulation
dc.contributor.author | Könik, Tolga | en_US |
dc.contributor.author | Cem Say, A. C. | en_US |
dc.date.accessioned | 2006-09-08T19:37:20Z | |
dc.date.available | 2006-09-08T19:37:20Z | |
dc.date.issued | 2003-08 | en_US |
dc.identifier.citation | Könik, Tolga; Cem Say, A.C.; (2003). "Duration Consistency Filtering for Qualitative Simulation." Annals of Mathematics and Artificial Intelligence 38(4): 269-309. <http://hdl.handle.net/2027.42/41773> | en_US |
dc.identifier.issn | 1012-2443 | en_US |
dc.identifier.issn | 1573-7470 | en_US |
dc.identifier.uri | https://hdl.handle.net/2027.42/41773 | |
dc.description.abstract | We present two new qualitative reasoning formalisms, and use them in the construction of a new type of filtering mechanism for qualitative simulators. Our new sign algebra, SR1*, facilitates reasoning about relationships among the signs of collections of real numbers. The comparison calculus , built on top of SR1*, is a general framework that can be used to qualitatively compare the behaviors of two dynamic systems or two excerpts of the behavior of a single dynamic system at different situations. These tools enable us to improve the predictive performance of qualitative simulation algorithms. We show that qualitative simulators can make better use of their input to deduce significant amounts of qualitative information about the relative lengths of the time intervals in their output behavior predictions. Simple techniques employing concepts like symmetry, periodicity, and comparison of the circumstances during multiple traversals of the same region can be used to build a list of facts representing the deduced information about relative durations. The duration consistency filter eliminates spurious behaviors leading to inconsistent combinations of these facts. Surviving behaviors are annotated with richer qualitative descriptions. Used in conjunction with other spurious behavior elimination methods, this approach would increase the ability of qualitative simulators to handle more complex systems. | en_US |
dc.format.extent | 313475 bytes | |
dc.format.extent | 3115 bytes | |
dc.format.mimetype | application/pdf | |
dc.format.mimetype | text/plain | |
dc.language.iso | en_US | |
dc.publisher | Kluwer Academic Publishers; Springer Science+Business Media | en_US |
dc.subject.other | Computer Science | en_US |
dc.subject.other | Computer Science, General | en_US |
dc.subject.other | Artificial Intelligence (Incl. Robotics) | en_US |
dc.subject.other | Mathematics, General | en_US |
dc.subject.other | Nonlinear Dynamics, Complex Systems, Chaos, Neural Networks | en_US |
dc.subject.other | Qualitative Reasoning | en_US |
dc.subject.other | Qualitative Simulation | en_US |
dc.subject.other | Spurious Behavior Filtering | en_US |
dc.subject.other | Sign Algebra | en_US |
dc.subject.other | Qualitative Comparison | en_US |
dc.title | Duration Consistency Filtering for Qualitative Simulation | en_US |
dc.type | Article | en_US |
dc.subject.hlbsecondlevel | Science (General) | en_US |
dc.subject.hlbsecondlevel | Computer Science | en_US |
dc.subject.hlbtoplevel | Science | en_US |
dc.subject.hlbtoplevel | Engineering | en_US |
dc.description.peerreviewed | Peer Reviewed | en_US |
dc.contributor.affiliationum | Artificial Intelligence Lab., University of Michigan, Advanced Tech. Bldg., 1101 Beal Ave., Ann Arbor, MI, 48109-2110, USA | en_US |
dc.contributor.affiliationother | Department of Computer Engineering, Boğaziçi University, Bebek, 34342, İstanbul, Turkey | en_US |
dc.contributor.affiliationumcampus | Ann Arbor | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/41773/1/10472_2004_Article_5118515.pdf | en_US |
dc.identifier.doi | http://dx.doi.org/10.1023/A:1023080709134 | en_US |
dc.identifier.source | Annals of Mathematics and Artificial Intelligence | en_US |
dc.owningcollname | Interdisciplinary and Peer-Reviewed |
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