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Ticker: A system for incremental ASP-based stream reasoning*

Published online by Cambridge University Press:  23 August 2017

HARALD BECK ,
THOMAS EITER  and
CHRISTIAN FOLIE
HARALD BECK
Affiliation:
Institute of Information Systems, Vienna University of Technology, Favoritenstraße 9-11, A-1040 Vienna, Austria (e-mails: [email protected], [email protected], [email protected])
THOMAS EITER
Affiliation:
Institute of Information Systems, Vienna University of Technology, Favoritenstraße 9-11, A-1040 Vienna, Austria (e-mails: [email protected], [email protected], [email protected])
CHRISTIAN FOLIE
Affiliation:
Institute of Information Systems, Vienna University of Technology, Favoritenstraße 9-11, A-1040 Vienna, Austria (e-mails: [email protected], [email protected], [email protected])
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Abstract

In complex reasoning tasks, as expressible by Answer Set Programming (ASP), problems often permit for multiple solutions. In dynamic environments, where knowledge is continuously changing, the question arises how a given model can be incrementally adjusted relative to new and outdated information. This paper introduces Ticker, a prototypical engine for well-defined logical reasoning over streaming data. Ticker builds on a practical fragment of the recent rule-based language LARS, which extends ASP for streams by providing flexible expiration control and temporal modalities. We discuss Ticker's reasoning strategies: first, the repeated one-shot solving mode calls Clingo on an ASP encoding. We show how this translation can be incrementally updated when new data is streaming in or time passes by. Based on this, we build on Doyle's classic justification-based truth-maintenance system to update models of non-stratified programs. Finally, we empirically compare the obtained evaluation mechanisms.

Keywords

Stream reasoningAnswer set programmingNon-monotonic reasoning
Type
Regular Papers
Information
Theory and Practice of Logic Programming , Volume 17 , Special Issue 5-6: 33rd International Conference on Logic Programming , September 2017 , pp. 744 - 763
Copyright
Copyright © Cambridge University Press 2017 

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Footnotes

*

This research has been supported by the Austrian Science Fund (FWF) projects P26471 and W1255-N23.

References

Alviano, M., Dodaro, C. and Ricca, F. 2014. Anytime computation of cautious consequences in answer set programming. Theory and Practice of Logic Programming 14, 4–5, 755–770.Google Scholar
Anicic, D., Rudolph, S., Fodor, P. and Stojanovic, N. 2012. Stream reasoning and complex event processing in ETALIS. Semantic Web 3, 4, 397–407.Google Scholar
Babu, S. and Widom, J. 2001. Continuous queries over data streams. SIGMOD Record 3, 30, 109–120.Google Scholar
Barbieri, D. F., Braga, D., Ceri, S., Valle, E. D. and Grossniklaus, M. 2010. Incremental reasoning on streams and rich background knowledge. In Proc. of Semantic Web: Research and Applications, 7th Extended Semantic Web Conference, ESWC 2010, Part I, Heraklion, Crete, Greece, May 30–June 3, 2010, Aroyo, L., Antoniou, G., Hyvönen, E., Teije, A. ten, Stuckenschmidt, H., Cabral, L., and Tudorache, T., Eds. Lecture Notes in Computer Science, vol. 6088. Springer, 1–15.Google Scholar
Beck, H. 2017. Reviewing Justification-based Truth Maintenance Systems from a Logic Programming Perspective. Tech. Rep. INFSYS RR-1843-17-02, Institute of Information Systems, TU Vienna.Google Scholar
Beck, H., Bierbaumer, B., Dao-Tran, M., Eiter, T., Hellwagner, H. and Schekotihin, K. 2017. Stream reasoning-Based control of caching strategies in CCN routers. In Proc. of the IEEE International Conference on Communications, May 21–25, 2017, Paris, France, 1–6.Google Scholar
Beck, H., Dao-Tran, M. and Eiter, T. 2015. Answer update for rule-based stream reasoning. In Proc. of the 24th International Joint Conference on Artificial Intelligence (IJCAI-15), July 25–31, 2015, Buenos Aires, Argentina, Yang, Q. and Wooldridge, M., Eds. AAAI Press/IJCAI, 2741–2747.Google Scholar
Beck, H., Dao-Tran, M., Eiter, T. and Fink, M. 2015. LARS: A logic-based framework for analyzing reasoning over streams. In Proc. of 29th Conference on Artificial Intelligence (AAAI'15), January 25–30, 2015, Austin, Texas, USA, Bonet, B. and Koenig, S., Eds. AAAI Press, 1431–1438.Google Scholar
Dao-Tran, M., Eiter, T., Fink, M., Weidinger, G. and Weinzierl, A. 2012. Omiga: An open minded grounding on-the-fly answer set solver. In Proc. of Logics in Artificial Intelligence - 13th European Conference, JELIA 2012, Toulouse, France, September 26–28, 2012, del Cerro, L. F., Herzig, A., and Mengin, J., Eds. Lecture Notes in Computer Science, vol. 7519. Springer, 480–483.Google Scholar
Della Valle, E., Ceri, S., van Harmelen, F. and Fensel, D. 2009. It's a streaming world! Reasoning upon rapidly changing information. IEEE Intelligent Systems 24, 83–89.CrossRefGoogle Scholar
Do, T. M., Loke, S. W. and Liu, F. 2011. Answer set programming for stream reasoning. In Proc. of Advances in Artificial Intelligence - 24th Canadian Conference on Artificial Intelligence, Canadian AI 2011, St. John's, Canada, May 25–27, 2011, Butz, C. J. and Lingras, P., Eds. Lecture Notes in Computer Science, vol. 6657. Springer, 104–109.Google Scholar
Doyle, J. 1979. A truth maintenance system. Artificial Intelligence 12, 3, 231–272.CrossRefGoogle Scholar
Elkan, C. 1990. A rational reconstruction of nonmonotonic truth maintenance systems. Artificial Intelligence 43 2, 219–234.CrossRefGoogle Scholar
Gebser, M., Kaminski, R., Kaufmann, B. and Schaub, T. 2014. Clingo = ASP + control: Preliminary report. In Proc. of Technical Communications of the 30th International Conference on Logic Programming (ICLP'14), Leuschel, M. and Schrijvers, T., Eds. Theory and Practice of Logic Programming, Online Supplement.Google Scholar
Gebser, M., Kaminski, R., Obermeier, P. and Schaub, T. 2015. Ricochet robots reloaded: A case-study in multi-shot ASP solving. In Proc. of Advances in Knowledge Representation, Logic Programming, and Abstract Argumentation - Essays Dedicated to Gerhard Brewka on the Occasion of His 60th Birthday, Eiter, T., Strass, H., Truszczynski, M. and Woltran, S., Eds. Lecture Notes in Computer Science, vol. 9060. Springer, 17–32.Google Scholar
Gupta, A., Mumick, I. S. and Subrahmanian, V. S. 1993. Maintaining views incrementally. In Proc. of ACM SIGMOD International Conference on Management of Data, 157–166.Google Scholar
Lefèvre, C. and Nicolas, P. 2009. The first version of a new ASP solver: Asperix. In Proc. of Logic Programming and Nonmonotonic Reasoning, 10th International Conference, LPNMR 2009, Potsdam, Germany, September 14–18, 2009, Erdem, E., Lin, F., and Schaub, T., Eds. Lecture Notes in Computer Science, vol. 5753. Springer, 522–527.Google Scholar
Palù, A. D., Dovier, A., Pontelli, E. and Rossi, G. 2009. Answer set programming with constraints using lazy grounding. In Proc. of Logic Programming, 25th International Conference, ICLP 2009, Pasadena, CA, USA, July 14–17, 2009, Hill, P. M. and Warren, D. S., Eds. Lecture Notes in Computer Science, vol. 5649. Springer, 115–129.Google Scholar
Phuoc, D. L., Dao-Tran, M., Parreira, J. X. and Hauswirth, M. 2011. A native and adaptive approach for unified processing of linked streams and linked data. In Proc. of ISWC (1), 370–388.Google Scholar
Ren, Y. and Pan, J. Z. 2011. Optimising ontology stream reasoning with truth maintenance system. In Proc. of the 20th ACM Conference on Information and Knowledge Management, CIKM 2011, Glasgow, United Kingdom, October 24–28, 2011, Macdonald, C., Ounis, I., and Ruthven, I., Eds. ACM, 831–836.Google Scholar
Spring, N. T., Mahajan, R., Wetherall, D. and Anderson, T. E. 2004. Measuring ISP topologies with rocketfuel. IEEE/ACM Transaction Network 12 1, 2–16.CrossRefGoogle Scholar
Zaniolo, C. 2012. Logical foundations of continuous query languages for data streams. In Proc. of Datalog, 177–189.Google Scholar
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