Hostname: page-component-89b8bd64d-b5k59 Total loading time: 0 Render date: 2026-05-08T08:44:37.028Z Has data issue: false hasContentIssue false
  • English
  • Français

Simulating Dynamic Systems Using Linear Time Calculus Theories

Published online by Cambridge University Press:  21 July 2014

BART BOGAERTS ,
JOACHIM JANSEN ,
MAURICE BRUYNOOGHE ,
BROES DE CAT ,
JOOST VENNEKENS  and
MARC DENECKER
BART BOGAERTS
Affiliation:
Department of Computer Science, KU Leuven (e-mail: firstname.lastname@cs.kuleuven.be)
JOACHIM JANSEN
Affiliation:
Department of Computer Science, KU Leuven (e-mail: firstname.lastname@cs.kuleuven.be)
MAURICE BRUYNOOGHE
Affiliation:
Department of Computer Science, KU Leuven (e-mail: firstname.lastname@cs.kuleuven.be)
BROES DE CAT
Affiliation:
Department of Computer Science, KU Leuven (e-mail: firstname.lastname@cs.kuleuven.be)
JOOST VENNEKENS
Affiliation:
Department of Computer Science, KU Leuven (e-mail: firstname.lastname@cs.kuleuven.be)
MARC DENECKER
Affiliation:
Department of Computer Science, KU Leuven (e-mail: firstname.lastname@cs.kuleuven.be)
Get access Rights & Permissions [Opens in a new window]

Abstract

Dynamic systems play a central role in fields such as planning, verification, and databases. Fragmented throughout these fields, we find a multitude of languages to formally specify dynamic systems and a multitude of systems to reason on such specifications. Often, such systems are bound to one specific language and one specific inference task. It is troublesome that performing several inference tasks on the same knowledge requires translations of your specification to other languages. In this paper we study whether it is possible to perform a broad set of well-studied inference tasks on one specification. More concretely, we extend IDP3 with several inferences from fields concerned with dynamic specifications.

Keywords

Dynamic systemsprogressionsimulationknowledge base systeminferences

Information

Type
Regular Papers
Information
Theory and Practice of Logic Programming , Volume 14 , Special Issue 4-5: 30th International Conference on Logic Programming , July 2014 , pp. 477 - 492
Copyright
Copyright © Cambridge University Press 2014 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Article purchase

Temporarily unavailable

References

Alviano, M., Calimeri, F., Charwat, G., Dao-Tran, M., Dodaro, C., Ianni, G., Krennwallner, T., Kronegger, M., Oetsch, J., Pfandler, A., Pührer, J., Redl, C., Ricca, F., Schneider, P., Schwengerer, M., Spendier, L. K., Wallner, J. P., and Xiao, G. 2013. The fourth answer set programming competition: Preliminary report. In LPNMR, Cabalar, P. and Son, T. C., Eds. Lecture Notes in Computer Science, vol. 8148. Springer, 42–53.Google Scholar
Amadini, R., Gabbrielli, M., and Mauro, J. 2013. Features for building CSP portfolio solvers. arXiv:1308.0227 [cs.AI].Google Scholar
Amanda, C., Andrew, C., Olaya, A. G., Jimenez, S., Lopez, C. L., Sanner, S., and Yoon, S. 2012. A survey of the seventh international planning competition. AI Magazine 33, 1 (June), 1–8.Google Scholar
Apt, K. R. 2003. Principles of Constraint Programming. Cambridge University Press.CrossRefGoogle Scholar
Bogaerts, B. 2014. PacManID: an implementation of Pac-Man using the simulation inference. http://dtai.cs.kuleuven.be/krr/files/software/various/pacman.tar.gz Google Scholar
Bonner, A. J., Kifer, M., and Consens, M. 1993. Database programming in transaction logic. In In Proc. 4th Int. Workshop on Database Programming Languages. 309–337.CrossRefGoogle Scholar
Calimeri, F., Ianni, G., Ricca, F., Alviano, M., Bria, A., Catalano, G., Cozza, S., Faber, W., Febbraro, O., Leone, N., Manna, M., Martello, A., Panetta, C., Perri, S., Reale, K., Santoro, M. C., Sirianni, M., Terracina, G., and Veltri, P. 2011. The third answer set programming system competition: Preliminary report of the system competition track. In Proceedings of the International Conference on Logic Programming and Nonmonotonic Reasoning (LPNMR). Springer, 388–403.CrossRefGoogle Scholar
Cimatti, A., Clarke, E., Giunchiglia, E., Giunchiglia, F., Pistore, M., Roveri, M., Sebastiani, R., and Tacchella, A. 2002. NuSMV Version 2: An OpenSource Tool for Symbolic Model Checking. In Proc. International Conference on Computer-Aided Verification (CAV 2002). LNCS, vol. 2404. Springer, Copenhagen, Denmark.Google Scholar
De Cat, B., Bogaerts, B., Bruynooghe, M., and Denecker, M. 2014. Predicate logic as a modelling language: The IDP system. CoRR abs/1401.6312. Google Scholar
De Cat, B., Denecker, M., and Stuckey, P. 2012. Lazy model expansion by incremental grounding. In Proceedings of the 28th International Conference on Logic Programming – Technical Communications (ICLP'12), Dovier, A. and Costa, V. Santos, Eds. LIPIcs, vol. 17. Schloss Daghstuhl - Leibniz-Zentrum fuer Informatik, 201–211.Google Scholar
De Pooter, S., Wittocx, J., and Denecker, M. 2011. A prototype of a knowledge-based programming environment. CoRR abs/1108.5667.Google Scholar
Denecker, M. 2012. The FO(ċ) knowledge base system project: An integration project (invited talk). In ASPOCP.Google Scholar
Denecker, M. and Ternovska, E. 2008. A logic of nonmonotone inductive definitions. ACM Transactions on Computational Logic (TOCL) 9, 2 (Apr.), 14:1–14:52.CrossRefGoogle Scholar
Denecker, M. and Vennekens, J. 2008. Building a knowledge base system for an integration of logic programming and classical logic. In ICLP, García de la Banda, M. and Pontelli, E., Eds. LNCS, vol. 5366. Springer, 71–76.Google Scholar
Denecker, M. and Vennekens, J. 2014. The well-founded semantics is the principle of inductive definition, revisited. In KR. AAAI Press. Accepted.Google Scholar
Fitting, M. 1996. First-order logic and automated theorem proving (2nd ed.). Springer-Verlag New York, Inc., Secaucus, NJ, USA.CrossRefGoogle Scholar
Gebser, M., Grote, T., Kaminski, R., Obermeier, P., Sabuncu, O., and Schaub, T. 2012. Stream reasoning with answer set programming: Preliminary report. In KR, Brewka, G., Eiter, T., and McIlraith, S. A., Eds. AAAI Press, 613–617.Google Scholar
Gelfond, M. and Lifschitz, V. 1998. Action languages. Electron. Trans. Artif. Intell. 2, 193–210.Google Scholar
Ghallab, M., Isi, C. K., Penberthy, S., Smith, D. E., Sun, Y., and Weld, D. 1998. PDDL – The Planning Domain Definition Language. Tech. rep., CVC TR-98-003/DCS TR-1165, Yale Center for Computational Vision and Control.Google Scholar
Green, T. J., Aref, M., and Karvounarakis, G. 2012. Logicblox, platform and language: A tutorial. In Datalog, Barceló, P. and Pichler, R., Eds. LNCS, vol. 7494. Springer, 1–8.Google Scholar
Haufe, S., Schiffel, S., and Thielscher, M. 2012. Automated verification of state sequence invariants in general game playing. Artif. Intell. 187, 1–30.CrossRefGoogle Scholar
IDP 2013. The IDP system. http://dtai.cs.kuleuven.be/krr/software Google Scholar
IDPDraw 2012. IDPDraw: finite structure visualization. http://dtai.cs.kuleuven.be/krr/software/visualisation Google Scholar
Ierusalimschy, R., de Figueiredo, L. H., and Celes, W. 1996. Lua – an extensible extension language. Software: Practice and Experience 26, 6, 635–652.Google Scholar
Kaufmann, M., Moore, J. S., and Manolios, P. 2000. Computer-Aided Reasoning: An Approach. Kluwer Academic Publishers, Norwell, MA, USA.Google Scholar
Kowalski, R. A. and Sadri, F. 2013. Towards a logic-based unifying framework for computing. CoRR abs/1301.6905.Google Scholar
Kowalski, R. A. and Sergot, M. J. 1986. A logic-based calculus of events. New Generation Computing 4, 1, 67–95.CrossRefGoogle Scholar
Leuschel, M. and Butler, M. J. 2008. ProB: An automated analysis toolset for the B method. STTT 10, 2, 185–203.CrossRefGoogle Scholar
Lin, F. and Reiter, R. 1997. How to progress a database. Artif. Intell. 92, 1-2, 131–167.CrossRefGoogle Scholar
Mariën, M., Gilis, D., and Denecker, M. 2004. On the relation between ID-Logic and Answer Set Programming. In JELIA, Alferes, J. J. and Leite, J. A., Eds. LNCS, vol. 3229. Springer, 108–120.Google Scholar
Markov, A. A. 1906. Rasprostranenie zakona bol'shih chisel na velichiny, zavisyaschie drug ot druga. Izvestiya Fiziko-matematicheskogo obschestva pri Kazanskom universitete 2-ya seriya, 15, 135–156.Google Scholar
The Coq development team. 2004. The Coq proof assistant reference manual. LogiCal Project. Version 8.0.Google Scholar
McCarthy, J. and Hayes, P. J. 1969. Some philosophical problems from the standpoint of artificial intelligence. In Machine Intelligence 4, Meltzer, B. and Michie, D., Eds. Edinburgh University Press, 463–502.Google Scholar
Nemhauser, G. L. and Wolsey, L. A. 1988. Integer and Combinatorial Optimization. John Wiley and Sons, New York.CrossRefGoogle Scholar
Reiter, R. 2001. Knowledge in Action: Logical Foundations for Specifying and Implementing Dynamical Systems. MIT Press.CrossRefGoogle Scholar
Riazanov, A. and Voronkov, A. 2002. The design and implementation of vampire. AI Communications 15, 2-3, 91–110.Google Scholar
Shlyakhter, I., Seater, R., Jackson, D., Sridharan, M., and Taghdiri, M. 2003. Debugging overconstrained declarative models using unsatisfiable cores. In ASE. IEEE Computer Society, 94–105.Google Scholar
Sutcliffe, G. 2009. The TPTP problem library and associated infrastructure: The FOF and CNF parts, v3.5.0. Journal of Automated Reasoning 43, 4, 337–362.CrossRefGoogle Scholar
Sutcliffe, G. 2013. The 6th IJCAR Automated Theorem Proving System Competition - CASC-J6. AI Communications 26, 2, 211–223.CrossRefGoogle Scholar
Sutcliffe, G., Schulz, S., Claessen, K., and Baumgartner, P. 2012. The TPTP typed first-order form with arithmetic. In LPAR, Bjørner, N. and Voronkov, A., Eds. Lecture Notes in Computer Science, vol. 7180. Springer, 406–419.Google Scholar
Thielscher, M. 2011. A unifying action calculus. Artif. Intell. 175, 1 (Jan.), 120–141.CrossRefGoogle Scholar
van Ginkel, N. 2013. Pddl2IDP: a PDDL parser for IDP. http://dtai.cs.kuleuven.be/krr/files/software/various/pddl2idp.zip Google Scholar
Vardi, M. Y. 1986. Querying logical databases. Journal of Computer and System Sciences 33, 2, 142–160.CrossRefGoogle Scholar
Weidenbach, C., Dimova, D., Fietzke, A., Kumar, R., Suda, M., and Wischnewski, P. 2009. Spass version 3.5. In CADE, Schmidt, R. A., Ed. LNCS, vol. 5663. Springer, 140–145.Google Scholar
Wittocx, J., Mariën, M., and Denecker, M. 2008. The idp system: a model expansion system for an extension of classical logic. In LaSh, M. Denecker, Ed. 153–165.Google Scholar
Supplementary material: PDF

BOGAERTS et al.

Simulating Dynamic Systems Using Linear Time Calculus Theories

Download BOGAERTS et al.(PDF)
PDF 277.1 KB