Skip to main content
SpringerLink
Log in
Book cover

International Conference on Artificial Intelligence and Soft Computing

ICAISC 2017: Artificial Intelligence and Soft Computing pp 477–488Cite as

The Impact of the Number of Averaged Attacker’s Strategies on the Results Quality in Mixed-UCT

  • Conference paper
  • First Online:

  • 1946 Accesses

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10246))

Abstract

Mixed-UCT is a method for finding efficient defender’s mixed strategy in multi-act Security Games. This paper presents experimental evaluation of the impact of the number of averaged past attackers (APA) used to define the defender’s strategy on solution quality of the method. Specifically designed set of test games is proposed for evaluation of the Mixed-UCT method with different values of APA parameter. The results indicate that larger values of APA generally lead to faster convergence of the method, and in some cases also improve the results in terms of the expected defender’s payoff value.

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

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
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

Learn about institutional subscriptions

References

  1. Achterberg, T.: SCIP: solving constraint integer programs. Math. Program. Comput. 1(1), 1–41 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  2. An, B., Ordóñez, F., Tambe, M., Shieh, E., Yang, R., Baldwin, C., DiRenzo, J., Moretti, K., Maule, B., Meyer, G.: A deployed quantal response-based patrol planning system for the us coast guard. Interfaces 43(5), 400–420 (2013)

    Google Scholar 

  3. Auer, P., Cesa-Bianchi, N., Fischer, P.: Finite-time analysis of the multiarmed bandit problem. Mach. Learn. 47(2–3), 235–256 (2002)

    Article  MATH  Google Scholar 

  4. Browne, C., Powley, E., Whitehouse, D., Lucas, S., Cowling, P., Rohlfshagen, P., Tavener, S., Perez, D., Samothrakis, S., Colton, S.: A survey of monte carlo tree search methods. IEEE Trans. Comput. Intell. AI Games 4(1), 1–43 (2012)

    Article  Google Scholar 

  5. Delle Fave, F.M., Jiang, A.X., Yin, Z., Zhang, C., Tambe, M., Kraus, S., Sullivan, J.P.: Game-theoretic patrolling with dynamic execution uncertainty and a case study on a real transit system. JAIR 50, 321–367 (2014)

    MathSciNet  MATH  Google Scholar 

  6. Fang, F., Stone, P., Tambe, M.: When Security Games go green: Designing defender strategies to prevent poaching and illegal fishing. In: IJCAI (2015)

    Google Scholar 

  7. Jain, M., Tsai, J., Pita, J., Kiekintveld, C., Rathi, S., Tambe, M., Ordóñez, F.: Software assistants for randomized patrol planning for the LAX airport police and the federal air marshal service. Interfaces 40(4), 267–290 (2010)

    Article  Google Scholar 

  8. Karwowski, J., Mańdziuk, J.: A new approach to security games. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2015. LNCS (LNAI), vol. 9120, pp. 402–411. Springer, Cham (2015). doi:10.1007/978-3-319-19369-4_36

    Chapter  Google Scholar 

  9. Karwowski, J., Mańdziuk, J.: Mixed strategy extraction from UCT tree in security games. In: ECAI 2016, pp. 1746–1747. IOS Press (2016)

    Google Scholar 

  10. Kocsis, L., Szepesvári, C.: Bandit based monte-carlo planning. In: Fürnkranz, J., Scheffer, T., Spiliopoulou, M. (eds.) ECML 2006. LNCS (LNAI), vol. 4212, pp. 282–293. Springer, Heidelberg (2006). doi:10.1007/11871842_29

    Chapter  Google Scholar 

  11. Paruchuri, P., Pearce, J.P., Marecki, J., Tambe, M., Ordonez, F., Kraus, S.: Efficient algorithms to solve bayesian stackelberg games for security applications. In: AAAI, pp. 1559–1562 (2008)

    Google Scholar 

  12. Paruchuri, P., Pearce, J.P., Marecki, J., Tambe, M., Ordonez, F., Kraus, S.: Playing games for security: an efficient exact algorithm for solving bayesian stackelberg games. In: AAMAS, pp. 895–902 (2008)

    Google Scholar 

  13. Silver, D., Huang, A., Maddison, C.J., Guez, A., Sifre, L., van den Driessche, G., Schrittwieser, J., Antonoglou, I., Panneershelvam, V., Lanctot, M., Dieleman, S., Grewe, D., Nham, J., Kalchbrenner, N., Sutskever, I., Lillicrap, T., Leach, M., Kavukcuoglu, K., Graepel, T., Hassabis, D.: Mastering the game of go with deep neural networks and tree search. Nature 529, 484–503 (2016)

    Article  Google Scholar 

  14. Świechowski, M., Mańdziuk, J.: Self-adaptation of playing strategies in general game playing. IEEE Trans. Comput. Intell. AI Games 6(4), 367–381 (2014)

    Article  MATH  Google Scholar 

  15. Waledzik, K., Mańdziuk, J.: An automatically-generated evaluation function in general game playing. IEEE Trans. Comput. Intell. AI Games 6(3), 258–270 (2014)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Faculty of Mathematics and Information Science, Warsaw University of Technology, Koszykowa 75, 00-662, Warsaw, Poland

    Jan Karwowski & Jacek Mańdziuk

  2. School of Computer Science and Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore, 639798, Singapore

    Jacek Mańdziuk

Authors
  1. Jan Karwowski
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jacek Mańdziuk
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jan Karwowski .

Editor information

Editors and Affiliations

  1. Częstochowa University of Technology, Częstochowa, Poland

    Leszek Rutkowski

  2. Częstochowa University of Technology, Częstochowa, Poland

    Marcin Korytkowski

  3. Częstochowa University of Technology, Częstochowa, Poland

    Rafał Scherer

  4. AGH University of Science and Technology, Kraków, Poland

    Ryszard Tadeusiewicz

  5. University of California, Berkeley, California, USA

    Lotfi A. Zadeh

  6. University of Louisville, Louisville, Kentucky, USA

    Jacek M. Zurada

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this paper

Cite this paper

Karwowski, J., Mańdziuk, J. (2017). The Impact of the Number of Averaged Attacker’s Strategies on the Results Quality in Mixed-UCT. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2017. Lecture Notes in Computer Science(), vol 10246. Springer, Cham. https://doi.org/10.1007/978-3-319-59060-8_43

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-59060-8_43

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59059-2

  • Online ISBN: 978-3-319-59060-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation