Skip to main content

2016 | OriginalPaper | Buchkapitel

Continuous Collaboration for Changing Environments

verfasst von : Matthias Hölzl, Thomas Gabor

Erschienen in: Transactions on Foundations for Mastering Change I

Verlag: Springer International Publishing

Aktivieren Sie unsere intelligente Suche um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

Collective autonomic systems (CAS) are distributed collections of agents that collaborate to achieve the system’s goals but autonomously adapt their behavior. We present the teacher/student architecture for locally coordinated distributed learning and show that in certain scenarios the performance of a swarm using teacher/student learning can be significantly better than that of agents learning individually. Teacher/student learning serves as foundation for the continuous collaboration (CC) development approach. We introduce CC, relate it to the EDLC, a life cycle model for CAS, and show that CC embodies many of the principles proposed for developing CAS.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Fußnoten
1
Taking into account the different times at which students exchange information with teachers, the knowledge and strategies the students share are typically similar, not identical. This does not change the gist of the following discussion.
 
2
The careful reader may observe that the single robot takes only approximately 6 times as long as the swarm to reach its maximal performance, not more than 10 times as might be expected. This is an artifact of our learning schedule which learns only at the end of each episode, so that the single agent performs many more iterations of the DP algorithm before it reaches its maximum performance than the DP-learner and thus better exploits the data it has available. This means that the single agent can focus a larger percentage of its exploration on promising parts of the graph, thereby negating the advantages that the swarm has over a single learner. However, a swarm of 10 single learners would use 10 times the computational resources of a swarm with a DP-learner, which would justify running the DP-learner 10 times as frequently with corresponding improvements to the swarm’s performance.
 
3
Between episodes 30 and 50 the random modifications result in a graph in which some of the routes computed by the non-learning teachers are viable, therefore the performance is slightly better than in the other episodes in which the graph is damaged.
 
Literatur
1.
Zurück zum Zitat Andre, D.: Programmable reinforcement learning agents. Ph.D. thesis, University of California at Berkeley (2003) Andre, D.: Programmable reinforcement learning agents. Ph.D. thesis, University of California at Berkeley (2003)
2.
Zurück zum Zitat Ay, N., Der, R., Prokopenko, M.: Guided self-organization: perception-action loops of embodied systems. Theory Biosci. 131(3), 125–127 (2012)CrossRef Ay, N., Der, R., Prokopenko, M.: Guided self-organization: perception-action loops of embodied systems. Theory Biosci. 131(3), 125–127 (2012)CrossRef
3.
Zurück zum Zitat Belzner, L., Hölzl, M., Koch, N., Wirsing, M.: Collective autonomic systems: towards engineering principles and their foundations, July 2016 Belzner, L., Hölzl, M., Koch, N., Wirsing, M.: Collective autonomic systems: towards engineering principles and their foundations, July 2016
4.
Zurück zum Zitat Cheng, B., et al.: Software engineering for self-adaptive systems: a research roadmap. In: Cheng, B., de Lemos, R., Giese, H., Inverardi, P., Magee, J. (eds.) Software Engineering for Self-Adaptive Systems. LNCS, vol. 5525, pp. 1–26. Springer, Heidelberg (2009). doi:10.1007/978-3-642-02161-9_1 CrossRef Cheng, B., et al.: Software engineering for self-adaptive systems: a research roadmap. In: Cheng, B., de Lemos, R., Giese, H., Inverardi, P., Magee, J. (eds.) Software Engineering for Self-Adaptive Systems. LNCS, vol. 5525, pp. 1–26. Springer, Heidelberg (2009). doi:10.​1007/​978-3-642-02161-9_​1 CrossRef
5.
Zurück zum Zitat Claus, C., Boutilier, C.: The dynamics of reinforcement learning in cooperative multiagent systems. In: Proceedings of the 15th National/Tenth Conference on AI/Innovative Applications of AI, AAAI 1998/IAAI 1998, pp. 746–752. AAAI (1998) Claus, C., Boutilier, C.: The dynamics of reinforcement learning in cooperative multiagent systems. In: Proceedings of the 15th National/Tenth Conference on AI/Innovative Applications of AI, AAAI 1998/IAAI 1998, pp. 746–752. AAAI (1998)
6.
Zurück zum Zitat Colombo, A., Fontanelli, D., Legay, A., Palopoli, L., Sedwards, S.: Efficient customisable dynamic motion planning for assistive robots in complex human environments. J. Ambient Intell. Smart Environ. 7(5), 617–634 (2015)CrossRef Colombo, A., Fontanelli, D., Legay, A., Palopoli, L., Sedwards, S.: Efficient customisable dynamic motion planning for assistive robots in complex human environments. J. Ambient Intell. Smart Environ. 7(5), 617–634 (2015)CrossRef
7.
Zurück zum Zitat Fagin, R., Moses, Y., Vardi, M., Halpern, J.: Reasoning About Knowledge. MIT Press, Cambridge (2003)MATH Fagin, R., Moses, Y., Vardi, M., Halpern, J.: Reasoning About Knowledge. MIT Press, Cambridge (2003)MATH
8.
Zurück zum Zitat Ghallab, M., Nau, D.S., Traverso, P.: Automated Planning - Theory and Practice. Elsevier, Amsterdam (2004)MATH Ghallab, M., Nau, D.S., Traverso, P.: Automated Planning - Theory and Practice. Elsevier, Amsterdam (2004)MATH
9.
Zurück zum Zitat Hölzl, M., Gabor, T.: Continuous collaboration: a case study on the development of an adaptive cyber-physical system. In: Proceedings of the 1st International Workshop on Software Engineering for Smart Cyber-Physical Systems (SEsCPS). IEEE (2015) Hölzl, M., Gabor, T.: Continuous collaboration: a case study on the development of an adaptive cyber-physical system. In: Proceedings of the 1st International Workshop on Software Engineering for Smart Cyber-Physical Systems (SEsCPS). IEEE (2015)
10.
Zurück zum Zitat Hölzl, M., Gabor, T.: Reasoning and learning for awareness and adaptation. In: Wirsing et al. [29] Hölzl, M., Gabor, T.: Reasoning and learning for awareness and adaptation. In: Wirsing et al. [29]
11.
Zurück zum Zitat Hölzl, M., Koch, N., Puviani, M., Wirsing, M., Zambonelli, F.: The ensemble development life cycle and best practices for collective autonomic systems. In: Wirsing et al. [29] Hölzl, M., Koch, N., Puviani, M., Wirsing, M., Zambonelli, F.: The ensemble development life cycle and best practices for collective autonomic systems. In: Wirsing et al. [29]
12.
Zurück zum Zitat Karafotias, G., Haasdijk, E., Eiben, A.E.: An algorithm for distributed on-line, on-board evolutionary robotics. In: Proceedings of the 13th Annual Conference on Genetic and Evolutionary Computation, GECCO 2011, pp. 171–178. ACM, New York (2011) Karafotias, G., Haasdijk, E., Eiben, A.E.: An algorithm for distributed on-line, on-board evolutionary robotics. In: Proceedings of the 13th Annual Conference on Genetic and Evolutionary Computation, GECCO 2011, pp. 171–178. ACM, New York (2011)
14.
Zurück zum Zitat Marzinotto, A., Colledanchise, M., Smith, C., Ögren, P.: Towards a unified behavior trees framework for robot control. In: 2014 IEEE International Conference on Robotics and Automation, ICRA 2014, Hong Kong, pp. 5420–5427. IEEE (2014) Marzinotto, A., Colledanchise, M., Smith, C., Ögren, P.: Towards a unified behavior trees framework for robot control. In: 2014 IEEE International Conference on Robotics and Automation, ICRA 2014, Hong Kong, pp. 5420–5427. IEEE (2014)
15.
Zurück zum Zitat Millington, I., Funge, J.: Artificial Intelligence for Games, 2nd edn. Morgan Kaufmann, San Francisco (2009) Millington, I., Funge, J.: Artificial Intelligence for Games, 2nd edn. Morgan Kaufmann, San Francisco (2009)
17.
Zurück zum Zitat Ogren, P.: Increasing modularity of UAV control systems using computer game behavior trees. In: AIAA Guidance, Navigation and Control Conference, Minneapolis, Minnesota, pp. 13–16 (2012) Ogren, P.: Increasing modularity of UAV control systems using computer game behavior trees. In: AIAA Guidance, Navigation and Control Conference, Minneapolis, Minnesota, pp. 13–16 (2012)
18.
Zurück zum Zitat Shalev-Shwartz, S., Ben-David, S.: Understanding Machine Learning: From Theory to Algorithms. Cambridge University Press, New York (2014)CrossRefMATH Shalev-Shwartz, S., Ben-David, S.: Understanding Machine Learning: From Theory to Algorithms. Cambridge University Press, New York (2014)CrossRefMATH
19.
Zurück zum Zitat Shoham, Y., Leyton-Brown, K.: Multiagent Systems: Algorithmic, Game-Theoretic, and Logical Foundations. Cambridge University Press, New York (2008)CrossRefMATH Shoham, Y., Leyton-Brown, K.: Multiagent Systems: Algorithmic, Game-Theoretic, and Logical Foundations. Cambridge University Press, New York (2008)CrossRefMATH
20.
Zurück zum Zitat Sigmund, K.: A survey of replicator equations. In: Casti, J.L., Karlqvist, A. (eds.) Complexity, Language, and Life: Mathematical Approaches. Biomathematics, vol. 16, pp. 88–104. Springer, Heidelberg (1986)CrossRef Sigmund, K.: A survey of replicator equations. In: Casti, J.L., Karlqvist, A. (eds.) Complexity, Language, and Life: Mathematical Approaches. Biomathematics, vol. 16, pp. 88–104. Springer, Heidelberg (1986)CrossRef
21.
Zurück zum Zitat Sutton, R.S., Barto, A.G.: Reinforcement Learning. MIT Press, Cambridge (1998) Sutton, R.S., Barto, A.G.: Reinforcement Learning. MIT Press, Cambridge (1998)
22.
Zurück zum Zitat Thrun, S., Burgard, W., Fox, D.: Probabilistic Robotics. MIT Press, Cambridge (2005)MATH Thrun, S., Burgard, W., Fox, D.: Probabilistic Robotics. MIT Press, Cambridge (2005)MATH
23.
Zurück zum Zitat Vapnik, V.: The Nature of Statistical Learning Theory. Information Science and Statistics. Springer, New York (2013)MATH Vapnik, V.: The Nature of Statistical Learning Theory. Information Science and Statistics. Springer, New York (2013)MATH
24.
Zurück zum Zitat Vapnik, V.N.: Statistical Learning Theory. Wiley-Interscience, New York (1998)MATH Vapnik, V.N.: Statistical Learning Theory. Wiley-Interscience, New York (1998)MATH
25.
Zurück zum Zitat Watson, R.A., Ficici, S.G., Pollack, J.B.: Embodied evolution: distributing an evolutionary algorithm in a population of robots. Robot. Auton. Syst. 39(1), 1–18 (2002)CrossRef Watson, R.A., Ficici, S.G., Pollack, J.B.: Embodied evolution: distributing an evolutionary algorithm in a population of robots. Robot. Auton. Syst. 39(1), 1–18 (2002)CrossRef
26.
Zurück zum Zitat Weiss, G. (ed.): Multiagent Systems, 2nd edn. MIT Press, Cambridge (2013) Weiss, G. (ed.): Multiagent Systems, 2nd edn. MIT Press, Cambridge (2013)
27.
Zurück zum Zitat Wiegand, R.P.: An analysis of cooperative coevolutionary algorithms. Ph.D. thesis, George Mason University (2003) Wiegand, R.P.: An analysis of cooperative coevolutionary algorithms. Ph.D. thesis, George Mason University (2003)
28.
Zurück zum Zitat Wiering, M., van Otterlo, M.: Reinforcement Learning: State-of-the-Art. Adaptation, Learning, and Optimization, vol. 12. Springer, Heidelberg (2012) Wiering, M., van Otterlo, M.: Reinforcement Learning: State-of-the-Art. Adaptation, Learning, and Optimization, vol. 12. Springer, Heidelberg (2012)
29.
Zurück zum Zitat Wirsing, M., Hölzl, M., Koch, N., Mayer, P. (eds.): Software Engineering for Collective Autonomic Systems: Results of the ASCENS Project. LNCS, vol. 8998. Springer, Heidelberg (2015) Wirsing, M., Hölzl, M., Koch, N., Mayer, P. (eds.): Software Engineering for Collective Autonomic Systems: Results of the ASCENS Project. LNCS, vol. 8998. Springer, Heidelberg (2015)
Metadaten
Titel
Continuous Collaboration for Changing Environments
verfasst von
Matthias Hölzl
Thomas Gabor
Copyright-Jahr
2016
DOI
https://doi.org/10.1007/978-3-319-46508-1_11