Skip to main content

Rigorous Engineering of Collective Adaptive Systems Introduction to the 4th Track Edition

  • Conference paper
  • First Online:
Leveraging Applications of Formal Methods, Verification and Validation. Adaptation and Learning (ISoLA 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13703))

Included in the following conference series:

  • 465 Accesses

Abstract

A collective adaptive system consists of collaborating entities that are able to adapt in real-time to dynamically changing and open environments and changing needs. Rigorous engineering requires appropriate methods and tools to help ensure that a collective adaptive system lives up to its intended purpose. This note provides an introduction to the 4th edition of the track “Rigorous Engineering of Collective Adaptive Systems” and briefly introduces the panel discussion and its 22 scientific contributions, structured into eight thematic sessions: Design and Validation of Autonomous Systems, Computing with Bio-inspired Communication, New System Models and Tools for Ensembles, Large Ensembles and Collective Dynamics, On the Borderline between Collective Stupidity and Collective Intelligence, Machine Learning for Collective Adaptive Systems, Programming and Analysing Ensembles, and Tools for Formal Analysis and Design.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 59.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 79.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Alberts, E., Gerostathopoulos, I.: Measuring convergence inertia: online learning in self-adaptive systems with context shifts. In: Margaria, T., Steffen, B. (eds.) ISoLA 2022, LNCS 13703, pp. 231–248. Springer, Heidelberg (2022)

    Google Scholar 

  2. Audrito, G., Damiani, F., Torta, G.: Bringing aggregate programming towards the cloud. In: Margaria, T., Steffen, B. (eds.) ISoLA 2022, LNCS 13703, pp. 301–317. Springer, Heidelberg (2022)

    Google Scholar 

  3. Bartoletti, M., Chiang, J., Junttila, T., Lafuente, A.L., Mirelli, M., Vandin, A.: Formal analysis of lending pools in decentralized finance. In: Margaria, T., Steffen, B. (eds.) ISoLA 2022, LNCS 13703, pp. 335–355. Springer, Heidelberg (2022)

    Google Scholar 

  4. Bellomo, N., et al.: What is life? a perspective of the mathematical kinetic theory of active particles. Math. Models Methods Appl. Sci. 31(9), 1821–1866 (2021)

    Google Scholar 

  5. Bortolussi, L., Cairoli, F., Paoletti, N., Smolka, S.A., Stoller, S.D.: Neural predictive monitoring and a comparison of frequentist and Bayesian approaches. Int. J. Softw. Tools Technol. Transfer 23(4), 615–640 (2021). https://doi.org/10.1007/s10009-021-00623-1

    Article  Google Scholar 

  6. Bozga, M., Sifakis, J.: Correct by design coordination of autonomous driving systems. In: Margaria, T., Steffen, B. (eds.) ISoLA 2022, LNCS 13703, pp. 13–29. Springer, Heidelberg (2022)

    Google Scholar 

  7. Brandstätter, A., Smolka, S.A., Stoller, S.D., Tiwari, A., Grosu, R.: Towards drone flocking using relative distance measurements. In: Margaria, T., Steffen, B. (eds.) ISoLA 2022, LNCS 13703, pp. 97–109. Springer, Heidelberg (2022)

    Google Scholar 

  8. Bureš, T., et al.: Attuning adaptation rules via a rule-specific neural network. In: Margaria, T., Steffen, B. (eds.) ISoLA 2022, LNCS 13703, pp. 215–230. Springer, Heidelberg (2022)

    Google Scholar 

  9. Bures, T., Gerostathopoulos, I., Hnětynka, P., Keznikl, J., Kit, M., Plášil, F.: DEECO: an ensemble-based component system. In: Kruchten, P., Giannakopoulou, D., Tivoli, M. (eds.) CBSE 2013, Proceedings of the 16th ACM SIGSOFT Symposium on Component Based Software Engineering, part of Comparch 2013, Vancouver, BC, Canada, 17–21 June 2013, pp. 81–90. ACM (2013)

    Google Scholar 

  10. Cairoli, F., Paoletti, N., Bortolussi, L.: Neural predictive monitoring for collective adaptive systems. In: Margaria, T., Steffen, B. (eds.) ISoLA 2022, LNCS 13703, pp. 30–46. Springer, Heidelberg (2022)

    Google Scholar 

  11. De Nicola, R., Di Stefano, L., Inverso, O., Valiani, S.: Modelling flocks of birds from the bottom u. In: Margaria, T., Steffen, B. (eds.) ISoLA 2022, LNCS 13703, pp. 82–96. Springer, Heidelberg (2022)

    Google Scholar 

  12. De Nicola, R., Jähnichen, S., Wirsing, M.: Rigorous engineering of collective adaptive systems: special section. Int. J. Softw. Tools Technol. Transfer 22(4), 389–397 (2020). https://doi.org/10.1007/s10009-020-00565-0

    Article  Google Scholar 

  13. De Nicola, R., Jähnichen, S., Wirsing, M.: Rigorous engineering of collective adaptive systems - introduction to the 2nd track edition. In: [28], pp. 3–12 (2018)

    Google Scholar 

  14. Fettke, P., Reisig, W.: Discrete models of continuous behavior of collective adaptive systems. In: Margaria, T., Steffen, B. (eds.) ISoLA 2022, LNCS 13703, pp. 65–81. Springer, Heidelberg (2022)

    Google Scholar 

  15. Hennicker, R., Knapp, A., Wirsing, M.: Epistemic ensembles. In: Margaria, T., Steffen, B. (eds.) ISoLA 2022, LNCS 13703, pp. 110–126. Springer, Heidelberg (2022)

    Google Scholar 

  16. Hennicker, R., Wirsing, M.: Dynamic logic for ensembles. In: [28], pp. 32–47 (2018)

    Google Scholar 

  17. Hennicker, R., Wirsing, M.: A dynamic logic for systems with predicate-based communication. In: [29], pp. 224–242 (2020)

    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.) Software-Intensive Systems and New Computing Paradigms. LNCS, vol. 5380, pp. 1–44. Springer, Heidelberg (2008). https://doi.org/10.1007/978-3-540-89437-7_1

    Chapter  MATH  Google Scholar 

  19. Jähnichen, S., Wirsing, M.: Rigorous engineering of collective adaptive systems - track introduction. In: [27], pp. 535–538 (2016)

    Google Scholar 

  20. Kernbach, S., Schmickl, T., Timmis, J.: Collective adaptive systems: challenges beyond evolvability. CoRR abs/1108.5643 (2011)

    Google Scholar 

  21. Lee, J., Kim, S., Bae, K., Ölveczky, P.C.: Hybrid SynchAADL: modeling and formal analysis of virtually synchronous CPSs in AADL. In: Silva, A., Leino, K.R.M. (eds.) CAV 2021. LNCS, vol. 12759, pp. 491–504. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-81685-8_23

    Chapter  Google Scholar 

  22. Lee, J., Kim, S., Bae, K., Ölveczky, P.C.: An extension of HybridSynchAADL and its application to collaborating autonomous UAVs. In: Margaria, T., Steffen, B. (eds.) ISoLA 2022, LNCS 13703, pp. 47–64. Springer, Heidelberg (2022)

    Google Scholar 

  23. Leguizamon-Robayo, A., Tschaikowski, M.: Efficient estimation of agent networks. In: Margaria, T., Steffen, B. (eds.) ISoLA 2022, LNCS 13703, pp. 199–214. Springer, Heidelberg (2022)

    Google Scholar 

  24. Lion, B., Arbab, F., Talcott, C.L.: A semantic model for interacting cyber-physical systems. In: Lange, J., Mavridou, A., Safina, L., Scalas, A. (eds.), Proceedings of 14th Interaction and Concurrency Experience, ICE 2021, vol. 347 of EPTCS, pp. 77–95 (2021)

    Google Scholar 

  25. Lion, B., Arbab, F., Talcott, C.L.: A rewriting framework for cyber-physical systems. In: Margaria, T., Steffen, B. (eds.) ISoLA 2022, LNCS 13703, pp. 356–372. Springer, Heidelberg (2022)

    Google Scholar 

  26. Margaria, T., Steffen, B. (eds.): ISoLA 2014, Part I. LNCS, vol. 8802. Springer, Heidelberg (2014). https://doi.org/10.1007/978-3-662-45234-9

    Book  Google Scholar 

  27. Margaria, T., Steffen, B.: Erratum to: leveraging applications of formal methods, verification and validation. In: Margaria, T., Steffen, B. (eds.) ISoLA 2016, Part I. LNCS, vol. 9952, pp. E1–E1. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-47166-2_67

    Chapter  Google Scholar 

  28. Margaria, T., Steffen, B. (eds.): ISoLA 2018, Part III. LNCS, vol. 11246. Springer, Cham (2018). https://doi.org/10.1007/978-3-030-03424-5

    Book  Google Scholar 

  29. Margaria, T., Steffen, B. (eds.): ISoLA 2020, Part II. LNCS, vol. 12477. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-61470-6

    Book  Google Scholar 

  30. Monica, S., Bergenti, F., Zambonelli, F.: Towards a kinetic framework to model the collective dynamics of large agent systems. In: Margaria, T., Steffen, B. (eds.) ISoLA 2022, LNCS 13703, pp. 165–180. Springer, Heidelberg (2022)

    Google Scholar 

  31. Murgia, M., Pinciroli, R., Trubiani, C., Tuosto, E.: On model-based performance analysis of collective adaptive systems. In: Margaria, T., Steffen, B. (eds.) ISoLA 2022, LNCS 13703, pp. 266–282. Springer, Heidelberg (2022)

    Google Scholar 

  32. Piterman, N., Abd Alrahman, Y., Azzopardi, S.: Model checking reconfigurable interacting systems. In: Margaria, T., Steffen, B. (eds.) ISoLA 2022, LNCS 13703, pp. 373–389. Springer, Heidelberg (2022)

    Google Scholar 

  33. Ritz, F., et al.: Capturing dependencies within machine learning via a formal process model. In: Margaria, T., Steffen, B. (eds.) ISoLA 2022, LNCS 13703, pp. 249–265. Springer, Heidelberg (2022)

    Google Scholar 

  34. ter Beek, M., Basile, D., Ciancia, V.: An experimental toolchain for strategy synthesis with spatial properties. In: Margaria, T., Steffen, B. (eds.) ISoLA 2022, LNCS 13703, pp. 142–164. Springer, Heidelberg (2022)

    Google Scholar 

  35. Tiezzi, F., Bourr, K., Bettini, L., Pugliese, R.: Programming multi-robot systems with X-KLAIM. In: Margaria, T., Steffen, B. (eds.) ISoLA 2022, LNCS 13703, pp. 283–300. Springer, Heidelberg (2022)

    Google Scholar 

  36. Töpfer, M., Abdullah, M., Bureš, T., Hnětynka, P., Kruliš, M.: Ensemble-based modeling abstractions for modern self-optimizing systems. In: Margaria, T., Steffen, B. (eds.) ISoLA 2022, LNCS 13703, pp. 318–334. Springer, Heidelberg (2022)

    Google Scholar 

  37. Tschaikowski, M.: Over-approximation of fluid models. IEEE Trans. Autom. Control. 65(3), 999–1013 (2020)

    Article  MathSciNet  Google Scholar 

  38. Wirsing, M., De Nicola, R., Hölzl, M.M.: Rigorous engineering of autonomic ensembles - track introduction. In: [26], pp. 96–98 (2014)

    Google Scholar 

  39. Wirsing, M., De Nicola, R., Jähnichen, S.: Rigorous engineering of collective adaptive systems - introduction to the 3rd track edition. In: [29], pp. 161–170 (2020)

    Google Scholar 

  40. Wirsing, M., Hölzl, M., Koch, N., Mayer, P. (eds.): Software Engineering for Collective Autonomic Systems. LNCS, vol. 8998. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-16310-9

    Book  Google Scholar 

  41. Yifeng, C., Sanders, J.W.: A modal approach to consciousness of agents. In: Margaria, T., Steffen, B. (eds.) ISoLA 2022, LNCS 13703, pp. 127–141. Springer, Heidelberg (2022)

    Google Scholar 

Download references

Acknowledgements

As organisers of the track, we would like to thank all authors and panelists for their valuable contributions, all reviewers for their careful evaluations and constructive comments, and all participants of the track for lively discussions. We are also grateful to the ISOLA chairs Tiziana Margaria and Bernhard Steffen for giving us the opportunity to organise this track and to them and Springer–Verlag for providing us with the very helpful Equinocs conference system.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Martin Wirsing .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Wirsing, M., De Nicola, R., Jähnichen, S. (2022). Rigorous Engineering of Collective Adaptive Systems Introduction to the 4th Track Edition. In: Margaria, T., Steffen, B. (eds) Leveraging Applications of Formal Methods, Verification and Validation. Adaptation and Learning. ISoLA 2022. Lecture Notes in Computer Science, vol 13703. Springer, Cham. https://doi.org/10.1007/978-3-031-19759-8_1

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-19759-8_1

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-19758-1

  • Online ISBN: 978-3-031-19759-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics