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Adaptive Cognitive Agents: Updating Action Descriptions and Plans

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Multi-Agent Systems (EUMAS 2023)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 14282))

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Abstract

In this paper we present an extension of Belief-Desire-Intention agents which can adapt their performance in response to changes in their environment. We consider situations in which the agent’s actions no longer perform as anticipated. Our agents maintain explicit descriptions of the expected behaviour of their actions, are able to track action performance, learn new action descriptions and patch affected plans at runtime. Our main contributions are the underlying theoretical mechanisms for data collection about action performance, the synthesis of new action descriptions from this data and the integration with plan reconfiguration. The mechanisms are supported by a practical implementation to validate the approach.

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Notes

  1. 1.

    As noted, many BDI formalisms represent plans in a very similar fashion, so although we use a Gwendolen plan as an example here, the technique is general.

  2. 2.

    Code available at https://github.com/mcapl/mcapl/tree/reconfig_eumas.

References

  1. Antzoulatos, N., Castro, E., de Silva, L., Rocha, A.D., Ratchev, S., Barata, J.: A multi-agent framework for capability-based reconfiguration of industrial assembly systems. Int. J. Prod. Res. 55(10), 2950–2960 (2017)

    Article  Google Scholar 

  2. Arora, A., Fiorino, H., Pellier, D., Etivier, M., Pesty, S.: A review of learning planning action models. Knowl. Eng. Rev. 33, e20 (2018)

    Article  Google Scholar 

  3. Bordini, R.H., ubner, J.F.H., Wooldridge, M.: Programming Multi-agent Systems in AgentSpeak Using Jason (2007)

    Google Scholar 

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

  5. Borgo, S., Cesta, A., Orlandini, A., Umbrico, A.: A planning-based architecture for a reconfigurable manufacturing system. In: Proceedings of the Twenty-Sixth International Conference on International Conference on Automated Planning and Scheduling, ICAPS 2016, pp. 358–366. AAAI Press, London (2016)

    Google Scholar 

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

    Google Scholar 

  7. 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 

  8. Chen, I.M., Yang, G., Yeo, S.H.: Automatic modeling for modular reconfigurable robotic systems: theory and practice. In: Cubero, S. (ed.) Industrial Robotics, chap. 2. IntechOpen, Rijeka (2006)

    Google Scholar 

  9. 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 

  10. Cohen, P.R., Feigenbaum, E.A.: The Handbook of Artificial Intelligence: Volume 3, vol. 3. Butterworth-Heinemann (2014)

    Google Scholar 

  11. Dastani, M.: 2APL: a practical agent programming language. Auton. Agent. Multi-Agent Syst. 16, 214–248 (2008). https://doi.org/10.1007/s10458-008-9036-y

    Article  Google Scholar 

  12. 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 

  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 Sour. Softw. 3(24), 617 (2018)

    Article  Google Scholar 

  15. Dennis, L.A., Fisher, M., Lincoln, N.K., Lisitsa, A., Veres, S.M.: Practical verification of decision-making in agent-based autonomous systems. Autom. Softw. Eng. 23(3), 305–359 (2016)

    Article  Google Scholar 

  16. Dennis, L.A., Fisher, M., Webster, M.P., Bordini, R.H.: Model checking agent programming languages. Autom. Softw. Eng. 19(1), 5–63 (2012). https://doi.org/10.1007/s10515-011-0088-x

    Article  Google Scholar 

  17. Ferrando, A., Cardoso, R.C.: Safety shields, an automated failure handling mechanism for BDI agents. In: Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2022, pp. 1589–1591. International Foundation for Autonomous Agents and Multiagent Systems, Richland (2022). www.ifaamas.org/Proceedings/aamas2022/pdfs/p1589.pdf

  18. Fikes, R.E., Nilsson, N.J.: Strips: a new approach to the application of theorem proving to problem solving. Artif. Intell. 2(3), 189–208 (1971). https://doi.org/10.1016/0004-3702(71)90010-5, www.sciencedirect.com/science/article/pii/0004370271900105

  19. Fisher, M., et al.: An overview of verification and validation challenges for inspection robots. Robotics 10(2) (2021). https://doi.org/10.3390/robotics10020067, www.mdpi.com/2218-6581/10/2/67

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

    Article  MATH  Google Scholar 

  21. Guerra-Hernández, A., El Fallah-Seghrouchni, A., Soldano, H.: Learning in BDI multi-agent systems. In: Dix, J., Leite, J. (eds.) CLIMA 2004. LNCS (LNAI), vol. 3259, pp. 218–233. Springer, Heidelberg (2004). https://doi.org/10.1007/978-3-540-30200-1_12

    Chapter  MATH  Google Scholar 

  22. Harland, J., Morley, D.N., Thangarajah, J., Yorke-Smith, N.: An operational semantics for the goal life-cycle in BDI agents. Auton. Agent. Multi-Agent Syst. 28(4), 682–719 (2014). https://doi.org/10.1007/s10458-013-9238-9

    Article  Google Scholar 

  23. 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 (2009). https://doi.org/10.1007/978-0-387-89299-3_4

    Chapter  MATH  Google Scholar 

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

    Google Scholar 

  25. Luger, G.F.: Artificial Intelligence: Structures and Strategies for Complex Problem Solving, 6th edn. Addison-Wesley Publishing Company, USA (2008)

    Google Scholar 

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

    Google Scholar 

  27. Menghi, C., Tsigkanos, C., Pelliccione, P., Ghezzi, C., Berger, T.: Specification patterns for robotic missions. IEEE Trans. Softw. Eng. 47(10), 2208–2224 (2021). https://doi.org/10.1109/TSE.2019.2945329

    Article  Google Scholar 

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

    Google Scholar 

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

    Google Scholar 

  30. Rao, A.S., Georgeff, M.P.: An abstract architecture for rational agents. KR 92, 439–449 (1992)

    Google Scholar 

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

    Article  Google Scholar 

  32. Støy, K., Brandt, D., Christensen, D.J.: Self-reconfigurable Robots. MIT Press, Cambridge (2010)

    Google Scholar 

  33. Stringer, P., Cardoso, R.C., Dixon, C., Dennis, L.A.: Implementing durative actions with failure detection in GWENDOLEN. In: Alechina, N., Baldoni, M., Logan, B. (eds.) EMAS 2021. LNCS, vol. 13190, pp. 332–351. Springer, Cham (2022). https://doi.org/10.1007/978-3-030-97457-2_19

    Chapter  Google Scholar 

  34. 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

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

    Google Scholar 

  36. Younes, H.L.A., Simmons, R.G.: Solving generalized semi-Markov decision processes using continuous phase-type distributions. In: Proceedings of the AAAI, pp. 742–747. AAAI Press (2004)

    Google Scholar 

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Acknowledgements

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), “Future AI and Robotics for Space” (EP/R026092/1), and Computational Agent Responsibility (EP/W01081X/1) Hubs and the TAS Verifiability Node (EP/V026801). During the course of this work, Michael Fisher was supported by the Royal Academy of Engineering.

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Authors and Affiliations

  1. The University of Manchester, Manchester, UK

    Peter Stringer, Clare Dixon, Michael Fisher & Louise A. Dennis

  2. University of Aberdeen, Aberdeen, UK

    Rafael C. Cardoso

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  1. Peter Stringer
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  2. Rafael C. Cardoso
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  3. Clare Dixon
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  4. Michael Fisher
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Correspondence to Peter Stringer .

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  1. Télécom Paris, Paris, France

    Vadim Malvone

  2. Universitá degli Studi di Napoli Federico II, Naples, Italy

    Aniello Murano

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Stringer, P., Cardoso, R.C., Dixon, C., Fisher, M., Dennis, L.A. (2023). Adaptive Cognitive Agents: Updating Action Descriptions and Plans. In: Malvone, V., Murano, A. (eds) Multi-Agent Systems. EUMAS 2023. Lecture Notes in Computer Science(), vol 14282. Springer, Cham. https://doi.org/10.1007/978-3-031-43264-4_22

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  • DOI: https://doi.org/10.1007/978-3-031-43264-4_22

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