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Iterative Width Search for Multi Agent Privacy-Preserving Planning

  • Gabriele Bazzotti
  • Alfonso Emilio Gerevini
  • Nir Lipovetzky
  • Francesco Percassi
  • Alessandro SaettiEmail author
  • Ivan Serina
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11298)

Abstract

In multi-agent planning, preserving the agents’ privacy has become an increasingly popular research topic. In multi-agent privacy-preserving planning, agents jointly compute a plan that achieves mutual goals by keeping certain information private to the individual agents. Unfortunately, preserving the privacy of such information can severely restrict the accuracy of the heuristic functions used while searching for solutions. Recently, it has been shown that centralized planning based on Width-based search is a very effective approach over several benchmark domains, even when the search is driven by uninformed heuristics. In this paper, we investigate the usage of Width-based search in the context of (decentralised) multi-agent privacy-preserving planning, addressing the challenges related to the agents’ privacy and performance. An experimental study analyses the effectiveness of our techniques and compares them with the state-of-the-art.

References

  1. 1.
    Brafman, R.I., Domshlak, C.: From one to many: planning for loosely coupled multi-agent systems. In: Proceedings of the Eighteenth International Conference on Automated Planning and Scheduling, ICAPS, pp. 28–35 (2008)Google Scholar
  2. 2.
    Nissim, R., Brafman, R.I.: Distributed heuristic forward search for multi-agent planning. J. Artif. Intell. Res. 51(1), 293–332 (2014)MathSciNetCrossRefGoogle Scholar
  3. 3.
    Torreño, A., Onaindia, E., Sapena, Ó.: An approach to multi-agent planning with incomplete information. In: Proceedings of the 20th European Conference on Artificial Intelligence, ECAI, pp. 762–767 (2012)Google Scholar
  4. 4.
    Lipovetzky, N., Geffner, H.: Width and serialization of classical planning problems. In: 20th European Conference on Artificial Intelligence, ECAI 2012, pp. 540–545 (2012)Google Scholar
  5. 5.
    Brafman, R.I.: A privacy preserving algorithm for multi-agent planning and search. In: International Joint Conference on Artificial Intelligence, IJCAI, pp. 1530–1536 (2015)Google Scholar
  6. 6.
    Maliah, S., Shani, G., Stern, R.: Privacy preserving landmark detection. In: Proceedings of European Conference on Artificial Intelligence, ECAI, vol. 14 (2014)Google Scholar
  7. 7.
    Maliah, S., Stern, R., Shani, G.: Privacy preserving LAMA. In: Proceedings of the Fourth Workshop on Distributed and Multi-agent Planning, ICAPS, pp. 100–108 (2016)Google Scholar
  8. 8.
    Nissim, R., Apsel, U., Brafman, R.I.: Tunneling and decomposition-based state reduction for optimal planning. In: 20th European Conference on Artificial Intelligence, ECAI, pp. 624–629 (2012)Google Scholar
  9. 9.
    Nissim, R., Brafman, R.I.: Multi-agent A* for parallel and distributed systems. In: Proceedings of the Workshop on Heuristics and Search for Domain-Independent Planning, ICAPS, pp. 42–51 (2012)Google Scholar
  10. 10.
    Bonisoli, A., Gerevini, A.E., Saetti, A., Serina, I.: A privacy-preserving model for multi-agent propositional planning. J. Exp. Theor. Artif. Intell. (2018, in press)Google Scholar
  11. 11.
    Fišer, D., Štolba, M., Komenda, A.: MAPlan. In: Proceedings of the Competition of Distributed and Multi-agent Planners, ICAPS, pp. 8–10 (2015)Google Scholar
  12. 12.
    Bonet, B., Geffner, H.: Planning as heuristic search. Artif. Intell. 129(1–2), 5–33 (2001)MathSciNetCrossRefGoogle Scholar
  13. 13.
    Blum, A.L., Furst, M.L.: Fast planning through planning graph analysis. Artif. Intell. 90(1–2), 281–300 (1997)CrossRefGoogle Scholar
  14. 14.
    Bandres, W., Bonet, B., Geffner, H.: Planning with pixels in (almost) real time. In: AAAI (2018)Google Scholar
  15. 15.
    Katz, M., Lipovetzky, N., Moshkovich, D., Tuisov, A.: Adapting novelty to classical planning as heuristic search. In: ICAPS, pp. 172–180 (2017)Google Scholar
  16. 16.
    Lipovetzky, N., Geffner, H.: Best-first width search: exploration and exploitation in classical planning. In: Singh, S.P., Markovitch, S. (eds.) Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 4–9 February 2017, San Francisco, California, USA, pp. 3590–3596. AAAI Press (2017)Google Scholar
  17. 17.
    Sustrik, M.: nanomsg (2016). http://nanomsg.org/
  18. 18.
    Štolba, M., Komenda, A., Kovacs, D.L.: Competition of distributed and multiagent planners (2015). http://agents.fel.cvut.cz/codmap/
  19. 19.
    Štolba, M., Komenda, A., Kovacs, D.L.: Competition of distributed and multiagent planners (codmap). In: The International Planning Competition (WIPC-15), vol. 24 (2015)Google Scholar
  20. 20.
    Olaya, A., G., López C., L., Jiménez, S., C.: Deterministic part of the 7th International Planning Competition IPC7. In: ICAPS (2011). http://www.plg.inf.uc3m.es/ipc2011-deterministic
  21. 21.
    Štolba, M., Fišer, D., Komenda, A.: Admissible landmark heuristic for multi-agent planning. In: Proceedings of the Twenty-Fifth International Conference on Automated Planning and Scheduling, ICAPS (2015)Google Scholar
  22. 22.
    Bonet, B., Helmert, M.: Strengthening landmark heuristics via hitting sets. In: ECAI 2010–19th European Conference on Artificial Intelligence, pp. 329–334 (2010)Google Scholar
  23. 23.
    Štolba, M., Komenda, A.: Relaxation heuristics for multiagent planning. In: Proceedings of the Twenty-Fourth International Conference on Automated Planning and Scheduling, ICAPS, pp. 298–306 (2014)Google Scholar
  24. 24.
    Bonisoli, A., Gerevini, A.E., Saetti, A., Serina, I.: A privacy-preserving model for the multi-agent propositional planning problem. In: Proceedings of the Twenty-First European Conference on Artificial Intelligence, ECAI, pp. 973–974 (2014)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Gabriele Bazzotti
    • 1
  • Alfonso Emilio Gerevini
    • 1
  • Nir Lipovetzky
    • 2
  • Francesco Percassi
    • 1
  • Alessandro Saetti
    • 1
    Email author
  • Ivan Serina
    • 1
  1. 1.Dipartimento di Ingegneria dell’InformazioneUniversità degli Studi di BresciaBresciaItaly
  2. 2.School of Computing and Information SystemsThe University of MelbourneMelbourneAustralia

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