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Implementing Durative Actions with Failure Detection in Gwendolen

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Engineering Multi-Agent Systems (EMAS 2021)

Abstract

We present an extension of the semantics for action execution in the Gwendolen BDI programming language. This extension firstly explicitly assumes that actions have durations and, moreover, that the reasoning cycle of the agent can not be stopped while such an action is executing but needs to continue in order to monitor for important external events. Secondly, the extension assumes that actions may often fail and this needs to be detected. This forms part of a larger project to develop a framework plan/action adaptation within BDI agents in order to enable long-term autonomy. We have implemented the extension and demonstrate its operation in a simple case study.

This work has been supported by The University of Manchester’s Department of Computer Science and the EPSRC “Robotics and AI for Nuclear” (EP/R026084/1) and “Future AI and Robotics for Space” (EP/R026092/1) Hubs.

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Notes

  1. 1.

    For simplicity of presentation, we here treat the intention as a stack of deeds but it should be noted that more information, such as the goal to be achieved, is also included in the full semantics.

  2. 2.

    This process of creating a new intention is not of relevance to this paper, but allows a Gwendolen agent to react to changes in its beliefs – e.g., to avoid an obstacle.

  3. 3.

    It is possible the failure conditions could be used here a bit like pre-conditions in capabilities, but that would really be an abuse of the notation.

  4. 4.

    Many robot path planning algorithms will reach their target events but when integrated with high level decision-making it is often announced that the robot has reached another waypoint.

  5. 5.

    The implementation can be found in https://github.com/peterstringer/mcapl/tree/dev.

References

  1. Aitken, J.M., Veres, S.M., Shaukat, A., Gao, Y., Cucco, E., Dennis, L.A., Fisher, M., Kuo, J.A., Robinson, T., Mort, P.E.: Autonomous nuclear waste management. IEEE Intell. Syst. 33(6), 47–55 (2018)

    Article  Google Scholar 

  2. Boissier, O., Bordini, R.H., Hubner, J., Ricci, A.: Multi-agent Oriented Programming: Programming Multi-agent Systems Using JaCaMo. MIT Press, Cambridge (2020)

    Google Scholar 

  3. Bordini, R.H., Hübner, J.F.: Semantics for the Jason variant of AgentSpeak (Plan failure and some internal actions). In: ECAI, pp. 635–640 (2010). https://doi.org/10.3233/978-1-60750-606-5-635

  4. Bordini, R.H., El Fallah Seghrouchni, A., Hindriks, K., Logan, B., Ricci, A.: Agent programming in the cognitive era. Auton. Agents Multi-Agent Syst. 34(2), 1–31 (2020). https://doi.org/10.1007/s10458-020-09453-y

    Article  Google Scholar 

  5. Bratman, M.E.: Intentions, Plans, and Practical Reason. Harvard University Press, Cambridge (1987)

    Google Scholar 

  6. Cardoso, R.C., Dennis, L.A., Fisher, M.: Plan library reconfigurability in BDI agents. In: Dennis, L.A., Bordini, R.H., Lespérance, Y. (eds.) EMAS 2019. LNCS (LNAI), vol. 12058, pp. 195–212. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-51417-4_10

    Chapter  Google Scholar 

  7. Cardoso, R.C., Farrell, M., Luckcuck, M., Ferrando, A., Fisher, M.: Heterogeneous verification of an autonomous curiosity rover. In: Lee, R., Jha, S., Mavridou, A., Giannakopoulou, D. (eds.) NFM 2020. LNCS, vol. 12229, pp. 353–360. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-55754-6_20

    Chapter  Google Scholar 

  8. Cardoso, R.C., Ferrando, A.: A review of agent-based programming for multi-agent systems. Computers 10(2), 16 (2021). https://doi.org/10.3390/computers10020016

    Article  Google Scholar 

  9. Cardoso, R.C., Ferrando, A., Dennis, L.A., Fisher, M.: An interface for programming verifiable autonomous agents in ROS. In: Bassiliades, N., Chalkiadakis, G., de Jonge, D. (eds.) Multi-Agent Systems and Agreement Technologies, pp. 191–205. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-66412-1_13

    Chapter  Google Scholar 

  10. Cirillo, M., Karlsson, L., Saffiotti, A.: Human-aware task-planning: an application to mobile robots. ACM Trans. Intell. Syst. Technol. 1(2), 15 (2010)

    Article  Google Scholar 

  11. Dastani, M., van Birna Riemsdijk, M., Meyer, J.-J.C.: Programming multi-agent systems in 3APL. In: Bordini, R.H., Dastani, M., Dix, J., El Fallah Seghrouchni, A. (eds.) Multi-Agent Programming. MSASSO, vol. 15, pp. 39–67. Springer, Boston, MA (2005). https://doi.org/10.1007/0-387-26350-0_2

    Chapter  Google Scholar 

  12. Dennis, L., Fisher, M., Lisitsa, A., Lincoln, N., Veres, S.: Satellite control using rational agent programming. IEEE Intell. Syst. 25(3), 92–97 (2010). https://doi.org/10.1109/mis.2010.88

    Article  Google Scholar 

  13. Dennis, L.A.: Gwendolen semantics: 2017. Technical Report ULCS-17-001, University of Liverpool, Department of Computer Science (2017)

    Google Scholar 

  14. Dennis, L.A.: The MCAPL framework including the agent infrastructure layer and agent Java pathfinder. J. Open Source Softw. 3(24), 617 (2018). https://doi.org/10.21105/joss.00617. The Open Journal

  15. Dennis, L.A., Fisher, M.: Actions with durations and failures in BDI languages. In: ECAI. pp. 995–996 (2014). https://doi.org/10.3233/978-1-61499-419-0-995

  16. Ferber, J., Müller, J.P.: Influences and reaction: a model of situated multiagent systems. In: Proceedings of Second International Conference on Multi-Agent Systems (ICMAS-1996), pp. 72–79 (1996)

    Google Scholar 

  17. Fox, M., Long, D.: PDDL2.1: an extension to PDDL for expressing temporal planning domains. JAIR 20, 61–124 (2003)

    Article  Google Scholar 

  18. Harland, J., Morley, D.N., Thangarajah, J., Yorke-Smith, N.: An operational semantics for the goal life-cycle in BDI agents. Auton. Agents Multi-Agent Syst. 28(4), 682–719 (2013). https://doi.org/10.1007/s10458-013-9238-9

    Article  Google Scholar 

  19. Helleboogh, A., Vizzari, G., Uhrmacher, A., Michel, F.: Modeling dynamic environments in multi-agent simulation. Auton. Agents Multi-Agent Syst. 14(1), 87–116 (2007). https://doi.org/10.1007/s10458-006-0014-y

    Article  Google Scholar 

  20. Hindriks, K.V.: Programming rational agents in GOAL. In: El Fallah Seghrouchni, A., Dix, J., Dastani, M., Bordini, R.H. (eds.) Multi-Agent Programming, pp. 119–157. Springer, Boston, MA (2009). https://doi.org/10.1007/978-0-387-89299-3_4

    Chapter  MATH  Google Scholar 

  21. Hindriks, K.V.: Programming cognitive agents in goal (2021)

    Google Scholar 

  22. Logan, B.: An agent programming manifesto. Int. J. Agent-Oriented Softw. Eng. 6(2), 187–210 (2018)

    Article  Google Scholar 

  23. Mascardi, V., Demergasso, D., Ancona, D.: Languages for programming BDI-style agents: an overview. In: WOA, vol. 2005, pp. 9–15 (2005)

    Google Scholar 

  24. Weld, D.S.: Planning with durative actions in stochastic domains. JAIR 31, 33–82 (2008)

    Article  MathSciNet  Google Scholar 

  25. Rao, A.S., Georgeff, M.P.: Modeling agents within a BDI-Architecture. In: Proceedings of 2nd International Conference on Principles of Knowledge Representation and Reasoning (KR&R), pp. 473–484. Morgan Kaufmann (1991)

    Google Scholar 

  26. Rao, A.S., Georgeff, M.P.: An abstract architecture for rational agents. In: Proceedings of 3rd International Conference on Principles of Knowledge Representation and Reasoning (KR&R), pp. 439–449. Morgan Kaufmann (1992)

    Google Scholar 

  27. Ricci, A., Piunti, M., Viroli, M.: Environment programming in multi-agent systems: an artifact-based perspective. Auton. Agents Multi-Agent Syst. 23(2), 158–192 (2011). https://doi.org/10.1007/s10458-010-9140-7

    Article  Google Scholar 

  28. Ricci, A., Santi, A., Piunti, M.: Action and perception in agent programming languages: from exogenous to endogenous environments. In: Collier, R., Dix, J., Novák, P. (eds.) ProMAS 2010. LNCS (LNAI), vol. 6599, pp. 119–138. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-28939-2_7

    Chapter  Google Scholar 

  29. Russell, S., Norvig, P.: Artificial Intelligence, A Modern Approach, 2nd edn. Prentice Hall, Hoboken (2003)

    MATH  Google Scholar 

  30. Sardina, S., Padgham, L.: A BDI agent programming language with failure handling, declarative goals, and planning. Auton. Agents Multi-Agent Syst. 23(1), 18–70 (2011)

    Article  Google Scholar 

  31. Sierhuis, M.: Modeling and Simulating Work Practice. BRAHMS: a multiagent modeling and simulation language for work system analysis and design. Ph.D. Thesis, SWI, University of Amsterdam, SIKS Dissertation Series No. 2001–10 (2001)

    Google Scholar 

  32. Stocker, R., Sierhuis, M., Dennis, L., Dixon, C., Fisher, M.: A formal semantics for Brahms. In: Leite, J., Torroni, P., Ågotnes, T., Boella, G., van der Torre, L. (eds.) CLIMA 2011. LNCS (LNAI), vol. 6814, pp. 259–274. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-22359-4_18

    Chapter  Google Scholar 

  33. Stringer, P., Cardoso, R.C., Huang, X., Dennis, L.A.: Adaptable and verifiable BDI reasoning. In: Cardoso, R.C., Ferrando, A., Briola, D., Menghi, C., Ahlbrecht, T. (eds.) Proceedings of the First Workshop on Agents and Robots for reliable Engineered Autonomy, Virtual event, 4th September 2020. Electronic Proceedings in Theoretical Computer Science, vol. 319, pp. 117–125. Open Publishing Association (2020). https://doi.org/10.4204/EPTCS.319.9

  34. Troquard, N., Vieu, L.: Towards a logic of agency and actions with duration. Front. Artif. Intell. Appl. 141, 775 (2006)

    Google Scholar 

  35. Wooldridge, M.: An Introduction to Multiagent Systems. Wiley, New York (2002)

    Google Scholar 

  36. Wooldridge, M., Rao, A. (eds.): Foundations of Rational Agency. Applied Logic Series. Kluwer Academic Publishers (1999)

    Google Scholar 

  37. Younes, H.L.A., Simmons, R.G.: Solving generalized semi-Markov decision processes using continuous phase-type distributions. In: Proceedings of AAAI, p. 742 (2004)

    Google Scholar 

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Stringer, P., Cardoso, R.C., Dixon, C., Dennis, L.A. (2022). Implementing Durative Actions with Failure Detection in Gwendolen. In: Alechina, N., Baldoni, M., Logan, B. (eds) Engineering Multi-Agent Systems. EMAS 2021. Lecture Notes in Computer Science(), vol 13190. Springer, Cham. https://doi.org/10.1007/978-3-030-97457-2_19

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  • DOI: https://doi.org/10.1007/978-3-030-97457-2_19

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