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Simple Temporal Networks: A Practical Foundation for Temporal Representation and Reasoning (Invited Talk)

Authors Luke Hunsberger, Roberto Posenato



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Author Details

Luke Hunsberger
  • Department of Computer Science, Vassar College, Poughkeepsie, NY, USA
Roberto Posenato
  • Department of Computer Science, University of Verona, Italy

Acknowledgements

The open access publication of this article was supported by the Alpen-Adria-Universität Klagenfurt, Austria.

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Luke Hunsberger and Roberto Posenato. Simple Temporal Networks: A Practical Foundation for Temporal Representation and Reasoning (Invited Talk). In 28th International Symposium on Temporal Representation and Reasoning (TIME 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 206, pp. 1:1-1:5, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)
https://doi.org/10.4230/LIPIcs.TIME.2021.1

Abstract

Since Simple Temporal Networks (STNs) were first introduced in 1991, there have been numerous theoretic and algorithmic advances that have made them practical for a wide variety of applications. However, the presentation of most of the important advances have been scattered across numerous conference papers and journal articles. As a result, it is too easy for even experienced researchers to be unaware of results that could positively impact their work. In this talk we review the most important results about STNs for researchers in Artificial Intelligence who are interested in incorporating the management of time and temporal constraints into their projects.

Subject Classification

ACM Subject Classification
  • Computing methodologies → Temporal reasoning
  • Theory of computation → Network optimization
  • Theory of computation → Dynamic graph algorithms
  • Mathematics of computing → Graph algorithms
Keywords
  • Simple Temporal Networks
  • Consistency Checking
  • Restoring Consistency
  • Dispatchability
  • Temporal Decoupling Problem

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References

  1. Mitchell Ai-Chang, John Bresina, Len Charest, Adam Chase, Jennifer Cheng Jung Hsu, Ari Jhonson, Bob Kanefsky, Paul Morris, Kanna Rajan, Jeffrey Yglesias, Brian G. Chafin, William C. Dias, and Pierre F. Maldague. Mapgeri: Mixed-Initiative Planning and Scheduling for the Mars Exploration Rover Mission. IEEE Intelligent Systems, 19(1):8-12, 2004. URL: https://doi.org/10.1109/MIS.2004.1265878.
  2. Claudio Bettini, Sushil Jajodia, X. Sean Wang, and Duminda Wijesekera. Provisions and Obligations in Policy Rule Management. J. Netw. Syst. Manag., 11(3):351-372, 2003. URL: https://doi.org/10.1023/A:1025711105609.
  3. Claudio Bettini, Xiaoyang Sean Wang, and Sushil Jajodia. Temporal reasoning in workflow systems. Dist. & Paral. Data., 11(3):269-306, 2002. URL: https://doi.org/10.1023/A:1014048800604.
  4. James C. Boerkoel and Edmund H. Durfee. Distributed reasoning for multiagent simple temporal problems. J. of Artificial Intelligence Research, 47:95-156, 2013. URL: https://doi.org/10.1613/jair.3840.
  5. Vittorio Brusoni, Luca Console, Paolo Terenziani, and Barbara Pernici. Later: Managing temporal information efficiently. IEEE Expert. Syst. their Appl., 12(4):56-63, 1997. URL: https://doi.org/10.1109/64.608197.
  6. Massimo Cairo, Carlo Combi, Carlo Comin, Luke Hunsberger, Roberto Posenato, Romeo Rizzi, and Matteo Zavatteri. Incorporating Decision Nodes into Conditional Simple Temporal Networks. In 24th Int. Symp. on Temporal Representation and Reasoning (TIME-2017), 2017. Google Scholar
  7. Filippo Cavallo, Raffaele Limosani, Alessandro Manzi, Manuele Bonaccorsi, Raffaele Esposito, Maurizio Di Rocco, Federico Pecora, Giancarlo Teti, Alessandro Saffiotti, and Paolo Dario. Development of a Socially Believable Multi-Robot Solution from Town to Home. Cognit. Comput., 6(4):954-967, 2014. URL: https://doi.org/10.1007/s12559-014-9290-z.
  8. Amedeo Cesta, Gabriella Cortellessa, Simone Fratini, and Angelo Oddi. Developing an end-to-end planning application from a Timeline Representation Framework. In Proc. 21st Innov. Appl. Artif. Intell. Conf. IAAI-09, pages 66-71, 2009. Google Scholar
  9. Amedeo Cesta, Gabriella Cortellessa, Riccardo Rasconi, Federico Pecora, Massimiliano Scopelliti, and Lorenza Tiberio. Monitoring elderly people with the ROBOCARE domestic environment: Interaction synthesis and user evaluation. In Comput. Intell., volume 27, pages 60-82, 2011. URL: https://doi.org/10.1111/j.1467-8640.2010.00372.x.
  10. Steve Chien, Benjamin Smith, Gregg Rabideau, Nicola Muscettola, and Kanna Rajan. Automated planning and scheduling for goal-based autonomous spacecraft. IEEE Intell. Syst. Their Appl., 13(5):50-55, 1998. URL: https://doi.org/10.1109/5254.722362.
  11. Carlo Combi, Matteo Gozzi, Barbara Oliboni, Jose M. Juarez, and Roque Marin. Temporal similarity measures for querying clinical workflows. Artif. Intell. Med., 46(1):37-54, 2009. URL: https://doi.org/10.1016/j.artmed.2008.07.013.
  12. Carlo Combi and Roberto Posenato. Controllability in temporal conceptual workflow schemata. In BPM, pages 64-79, 2009. URL: https://doi.org/10.1007/978-3-642-03848-8_6.
  13. Carlo Comin and Romeo Rizzi. Dynamic consistency of conditional simple temporal networks via mean payoff games: a singly-exponential time dc-checking. In 22st Int. Symp. on Temporal Representation and Reasoning (TIME 2015), pages 19-28, 2015. URL: https://doi.org/10.1109/TIME.2015.18.
  14. Ali Dasdan. Provably efficient algorithms for resolving temporal and spatial difference constraint violations. ACM Trans. Des. Autom. Electron. Syst., 14(1):8:1-8:24, 2009. URL: https://doi.org/10.1145/1455229.1455237.
  15. Pedro Henrique de Rodrigues Quemel e Assis Santana, Tiago Vaquero, Cláudio Toledo, Andrew J. Wang, Cheng Fang, and Brian Charles Williams. PARIS: A Polynomial-Time, Risk-Sensitive Scheduling Algorithm for Probabilistic Simple Temporal Networks with Uncertainty. In 26th Int. Conf. on Automated Planning and Scheduling (ICAPS-2016), pages 267-275, 2016. Google Scholar
  16. Rina Dechter, Itay Meiri, and J. Pearl. Temporal Constraint Networks. Artificial Intelligence, 49(1-3):61-95, 1991. URL: https://doi.org/10.1016/0004-3702(91)90006-6.
  17. Georg Duftschmid, Silvia Miksch, and Walter Gall. Verification of temporal scheduling constraints in clinical practice guidelines. Artif. Intell. Med., 25(2):93-121, 2002. URL: https://doi.org/10.1016/S0933-3657(02)00011-8.
  18. A. Gerevini, A. Perini, and F. Ricci. Incremental algorithms for managing temporal constraints. In 8th IEEE Int. Conf. on Tools with Artificial Intelligence, pages 360-363, 1996. URL: https://doi.org/10.1109/TAI.1996.560477.
  19. Malik Ghallab, Dana Nau, and Paolo Traverso. Automated Planning: Theory and Practice. Elsevier, 2004. URL: https://doi.org/10.1016/B978-1-55860-856-6.X5000-5.
  20. Fredrik Heintz, Piotr Rudol, and Patrick Doherty. From images to traffic behavior - A UAV tracking and monitoring application. In FUSION 2007 - 2007 10th Int. Conf. Inf. Fusion, 2007. URL: https://doi.org/10.1109/ICIF.2007.4408103.
  21. Wolfgang Honig, T. K. Satish Kumar, Liron Cohen, Hang Ma, Hong Xu, Nora Ayanian, and Sven Koenig. Multi-agent path finding with kinematic constraints. In Proc. Int. Conf. Autom. Plan. Sched. ICAPS, pages 477-485. AAAI press, 2016. Google Scholar
  22. Luke Hunsberger. Algorithms for a temporal decoupling problem in multi-agent planning. In 8th Nat. Conf. on Artificial Intelligence (AAAI-2002), 2002. Google Scholar
  23. Luke Hunsberger, Roberto Posenato, and Carlo Combi. A Sound-and-Complete Propagation-based Algorithm for Checking the Dynamic Consistency of Conditional Simple Temporal Networks. In Fabio Grandi, Martin Lange, and Alessio Lomuscio, editors, 22nd Int. Symp. on Temporal Representation and Reasoning (TIME-2015), pages 4-18, 2015. URL: https://doi.org/10.1109/TIME.2015.26.
  24. Félix Ingrand, Solange Lemai-Chenevier, and Frederic Py. Decisional autonomy of planetary rovers. J. F. Robot., 24(7):559-580, 2007. URL: https://doi.org/10.1002/rob.20206.
  25. Phil Kim, Brian C. Williams, and Mark Abramson. Executing reactive, model-based programs through graph-based temporal planning. In IJCAI Int. Jt. Conf. Artif. Intell., pages 487-493, 2001. Google Scholar
  26. Steven J. Levine and Brian C. Williams. Concurrent plan recognition and execution for human-robot teams. In Proc. Int. Conf. Autom. Plan. Sched. ICAPS, pages 490-498. AAAI press, 2014. Google Scholar
  27. Conor McGann, Frederic Py, Kanna Rajan, Hans Thomas, Richard Henthorn, and Rob McEwen. A deliberative architecture for AUV control. In Proc. - IEEE Int. Conf. Robot. Autom., pages 1049-1054, 2008. URL: https://doi.org/10.1109/ROBOT.2008.4543343.
  28. Paul H. Morris, Nicola Muscettola, and Thierry Vidal. Dynamic control of plans with temporal uncertainty. In 17th Int. Joint Conf. on Artificial Intelligence (IJCAI-2001), pages 494-502, 2001. Google Scholar
  29. R. Morris, P. Morris, L. Khatib, and N. Yorke-Smith. Temporal constraint reasoning with preferences and probabilities. In Multidisciplinary Workshop on Advances in Preference Handling in IJCAI-2005, pages 150-155, 2005. Google Scholar
  30. N. Muscettola, P.P. Nayak, B. Pell, and B.C. Williams. Remote Agent: To boldly go where no AI system has gone before. Artificial Intelligence, 103(1-2):5-47, 1998. URL: https://doi.org/10.1016/s0004-3702(98)00068-x.
  31. Ernesto Nunes and Maria Gini. Multi-robot auctions for allocation of tasks with temporal constraints. In Proc. Natl. Conf. Artif. Intell., volume 3, pages 2110-2116. AI Access Foundation, 2015. Google Scholar
  32. A. Oddi and A. Cesta. Incremental forward checking for the disjunctive temporal problem. In European Conf. on Artificial Intelligence (ECAI-2000), 2000. Google Scholar
  33. Lian Ien Oei. Resolving Disruptions in Simple Temporal Problems. mathesis, Delft University of Technology, 2009. Google Scholar
  34. Léon Planken, Mathijs de Weerdt, and Neil Yorke-Smith. Incrementally Solving STNs by Enforcing Partial Path Consistency. In 20th Int. Conf. on Automated Planning and Scheduling (ICAPS-2010), pages 129-136, 2010. URL: https://ojs.aaai.org/index.php/ICAPS/article/view/13417.
  35. Léon R. Planken, Mathijs M. de Weerdt, and Cees Witteveen. Optimal temporal decoupling in multiagent systems. In 9th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS-2010), volume 1, pages 789-796, 2010. Google Scholar
  36. G. Ramalingam, J. Song, L. Joskowicz, and R. E. Miller. Solving Systems of Difference Constraints Incrementally. Algorithmica, 23(3):261-275, 1999. URL: https://doi.org/10.1007/PL00009261.
  37. Wheeler Ruml, Minh B. Do, and Markus P.J. Fromherz. On-line planning and scheduling for high-speed manufacturing. In ICAPS 2005 - Proc. 15th Int. Conf. Autom. Plan. Sched., pages 30-39, 2005. Google Scholar
  38. E Schwalb and Rina Dechter. Processing disjunctions in temporal constraint networks. Artificial Intelligence, 93(1-2):29-61, 1997. URL: https://doi.org/10.1016/S0004-3702(97)00009-X.
  39. Kostas Stergiou and Manolis Koubarakis. Backtracking algorithms for disjunctions of temporal constraints. Artif. Intell., 120(1):81-117, 2000. URL: https://doi.org/10.1016/S0004-3702(00)00019-9.
  40. Ioannis Tsamardinos, Nicola Muscettola, and Paul Morris. Fast Transformation of Temporal Plans for Efficient Execution. In 15th National Conf. on Artificial Intelligence (AAAI-1998), pages 254-261, 1998. Google Scholar
  41. Ioannis Tsamardinos, Thierry Vidal, and Martha E. Pollack. CTP: A new constraint-based formalism for conditional, temporal planning. Constraints, 8:365-388, 2003. URL: https://doi.org/10.1023/A:1025894003623.
  42. Thierry Vidal and Hélène Fargier. Contingent durations in temporal csps: from consistency to controllabilities. In 4th Int. Workshop on Temporal Representation and Reasoning (TIME-1997), pages 78-85, 1997. URL: https://doi.org/10.1109/TIME.1997.600786.
  43. Thierry Vidal and Hélène Fargier. Handling contingency in temporal constraint networks: from consistency to controllabilities. J. of Experimental & Theoretical Artificial Intelligence, 11(1):23-45, 1999. URL: https://doi.org/10.1080/095281399146607.
  44. Michel Wilson, Tomas Klos, Cees Witteveen, and Bob Huisman. Flexibility and decoupling in simple temporal networks. Artificial Intelligence, 214:26-44, 2014. URL: https://doi.org/10.1016/j.artint.2014.05.003.
  45. Hyun Joong Yoon and Doo Yong Lee. Online scheduling of integrated single-wafer processing tools with temporal constraints. IEEE Trans. Semicond. Manuf., 18(3):390-398, 2005. URL: https://doi.org/10.1109/TSM.2005.852103.
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