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Soft Agents: Exploring Soft Constraints to Model Robust Adaptive Distributed Cyber-Physical Agent Systems

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Software, Services, and Systems

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 8950))

Abstract

We are interested in principles for designing and building open distributed systems consisting of multiple cyber-physical agents, specifically, where a coherent global view is unattainable and timely consensus is impossible. Such agents attempt to contribute to a system goal by making local decisions to sense and effect their environment based on local information. In this paper we propose a model, formalized in the Maude rewriting logic system, that allows experimenting with and reasoning about designs of such systems. Features of the model include communication via sharing of partially ordered knowledge, making explicit the physical state as well as the cyber perception of this state, and the use of a notion of soft constraints developed by Martin Wirsing and his team to specify agent behavior. The paper begins with a discussion of desiderata for such models and concludes with a small case study to illustrate the use of the modeling framework.

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References

  1. Wirsing, M., Denker, G., Talcott, C., Poggio, A., Briesemeister, L.: A rewriting logic framework for soft constraints. In: Sixth International Workshop on Rewriting Logic and Its Applications (WRLA 2006). Electronic Notes in Theoretical Computer Science. Elsevier (2006)

    Google Scholar 

  2. Hölzl, M., Meier, M., Wirsing, M.: Which soft constraints do you prefer? In: Seventh International Workshop on Rewriting Logic and Its Applications (WRLA 2008). Electronic Notes in Theoretical Computer Science, Elsevier (2008)

    Google Scholar 

  3. Gadducci, F., Hölzl, M., Monreale, G.V., Wirsing, M.: Soft constraints for lexicographic orders. In: Castro, F., Gelbukh, A., González, M. (eds.) MICAI 2013, Part I. LNCS, vol. 8265, pp. 68–79. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

  4. Interlink project (last accessed November 15, 2014)

    Google Scholar 

  5. Bristeau, P.J., Callou, F., Vissiére, D., Petit, N., et al.: The navigation and control technology inside the ar. drone micro uav. In: 18th IFAC world congress, vol. 18, pp. 1477–1484 (2011)

    Google Scholar 

  6. Krajník, T., Vonásek, V., Fišer, D., Faigl, J.: AR-Drone as a Platform for Robotic Research and Education. In: Obdržálek, D., Gottscheber, A. (eds.) EUROBOT 2011. CCIS, vol. 161, pp. 172–186. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  7. Meng, L., Li, L., Veres, S.: Aerodynamic parameter estimation of an unmanned aerial vehicle based on extended kalman filter and its higher order approach. In: 2010 2nd International Conference on Advanced Computer Control (ICACC), vol. 5, pp. 526–531. IEEE (2010)

    Google Scholar 

  8. Yokoo, M., Durfee, E.H., Ishida, T., Kuwabara, K.: The distributed constraint satisfaction problem: Formalization and algorithms. IEEE Transactions on Formalization and algorithms. Knowledge and Data Engineering 10(5), 673–685 (1998)

    Article  Google Scholar 

  9. Modi, P.J., Shen, W.M., Tambe, M., Yokoo, M.: ADOPT: Asynchronous distributed constraint optimization with quality guarantees. Artificial Intelligence 161(1), 149–180 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  10. des Jardins, M.E., Durfee, E.H., Charles, L., Ortiz, J., Wolverton, M.J.: A survey of research in distributed, continual planning. AI Magazine 20(4), 13 (1999)

    Google Scholar 

  11. de Weerdt, M., Clement, B.: Introduction to planning in multiagent systems. Multiagent Grid Syst. 5(4), 345–355 (2009)

    Article  Google Scholar 

  12. Bullo, F., Cortés, J., Martínez, S.: Distributed Control of Robotic Networks. Applied Mathematics Series. Princeton University Press (2009), Electronically available at http://coordinationbook.info

  13. Petcu, A., Faltings, B.: A scalable method for multiagent constraint optimization. In: Proceedings of the 19th International Joint Conference on Artificial Intelligence, IJCAI 2005, pp. 266–271. Morgan Kaufmann Publishers Inc, San Francisco (2005)

    Google Scholar 

  14. Stehr, M.-O., Talcott, C., Rushby, J., Lincoln, P., Kim, M., Cheung, S., Poggio, A.: Fractionated software for networked cyber-physical systems: Research directions and long-term vision. In: Agha, G., Danvy, O., Meseguer, J. (eds.) Formal Modeling: Actors, Open Systems, Biological Systems. LNCS, vol. 7000, pp. 110–143. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  15. Stehr, M.-O., Kim, M., Talcott, C.: Partially ordered knowledge sharing and fractionated systems in the context of other models for distributed computing. In: Iida, S., Meseguer, J., Ogata, K. (eds.) Specification, Algebra, and Software. LNCS, vol. 8373, pp. 402–433. Springer, Heidelberg (2014)

    Chapter  Google Scholar 

  16. Brown, O., Eremenko, P.: The value proposition for fractionated space architectures. In: Proc. of AIAA, San Jose, CA (September 2006)

    Google Scholar 

  17. Clavel, M., Durán, F., Eker, S., Lincoln, P., Martí-Oliet, N., Meseguer, J., Talcott, C.: All About Maude - A High-Performance Logical Framework. LNCS, vol. 4350. Springer, Heidelberg (2007)

    MATH  Google Scholar 

  18. Hölzl, M., Rauschmayer, A., Wirsing, M.: Engineering of software-intensive systems: State of the art and research challenges. In: Wirsing, M., Banâtre, J.-P., Hölzl, M., Rauschmayer, A. (eds.) Soft-Ware Intensive Systems. LNCS, vol. 5380, pp. 1–44. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  19. Ascens: Autonomic service-component ensembles (last accessed: November 15, 2014)

    Google Scholar 

  20. Hölzl, M., Wirsing, M.: Towards a system model for ensembles. In: Agha, G., Danvy, O., Meseguer, J. (eds.) Formal Modeling: Actors, Open Systems, Biological Systems. LNCS, vol. 7000, pp. 241–261. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  21. Arbab, F., Santini, F.: Preference and similarity-based behavioral discovery of services. In: Formal Methods (2012)

    Google Scholar 

  22. Kim, M., Stehr, M.O., Talcott, C.: A distributed logic for networked cyber-physical systems. Science of Computer Programming (2012)

    Google Scholar 

  23. Choi, J.S., McCarthy, T., Yadav, M., Kim, M., Talcott, C., Gressier-Soudan, E.: Application patterns for cyber-physical systems. In: Cyber-physical Systems Networks and Applications (2013)

    Google Scholar 

  24. Ölveczky, P.C., Meseguer, J.: Semantics and pragmatics of real-time maude. Higher-Order and Symbolic Computation 20(1-2), 161–196 (2007)

    Article  MATH  Google Scholar 

  25. Nielson, H.R., Nielson, F., Vigo, R.: A calculus for quality. In: Păsăreanu, C.S., Salaün, G. (eds.) FACS 2012. LNCS, vol. 7684, pp. 188–204. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

  26. Nielson, H.R., Nielson, F.: Safety versus security in the quality calculus. In: Liu, Z., Woodcock, J., Zhu, H. (eds.) Theories of Programming and Formal Methods. LNCS, vol. 8051, pp. 285–303. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

  27. Stehr, M.O., Talcott, C.: Planning and learning algorithms for routing in disruption-tolerant networks. In: MILCOM 2008. IEEE (2008)

    Google Scholar 

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Talcott, C., Arbab, F., Yadav, M. (2015). Soft Agents: Exploring Soft Constraints to Model Robust Adaptive Distributed Cyber-Physical Agent Systems. In: De Nicola, R., Hennicker, R. (eds) Software, Services, and Systems. Lecture Notes in Computer Science, vol 8950. Springer, Cham. https://doi.org/10.1007/978-3-319-15545-6_18

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  • DOI: https://doi.org/10.1007/978-3-319-15545-6_18

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-15544-9

  • Online ISBN: 978-3-319-15545-6

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