Abstract
This research introduces a spatio-temporal planning framework whose objective is to simulate a sailing yacht match race. The race is a duel in which strategy and tactics play a major role as sailors continuously have to take decisions according to wind variations and opponent’s locations and actions. We introduce a decision-aid framework based on a stochastic game approach grounded on an action-oriented model that replicates yachts’ behaviors. The objective is to replicate as closely as possible the respective behaviors and navigation decisions taken by yachts competitors. The proposed formalism has been implemented and is illustrated by a sample race example .
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Philpott, A., Henderson, S.G., Teirney, D.: A simulation model for predicting yacht match race outcomes. Oper. Res. 52(1), 1–16 (2004). INFORMS
Philpott, A.: Stochastic optimization and yacht racing. Appl. Stochast. Program. 5, 315–336 (2005)
Dalang, C.R., Dumas, F., Sardy, S., Morgenthaler, S., Vila, J.: Stochastic optimization of sailing trajectories in an upwind regatta. J. Oper. Res. Soc. (2014). Palgrave Macmillan
Martin, D., Beck, R.: PCSAIL, a velocity prediction program for a home computer. In: The 15th Cheasapeake Sailing Yacht Symposium, vol. 100 (2001)
Ferguson, D.S., Elinas, P.: A Markov decision process model for strategic decision making in sailboat racing. In: Butz, C., Lingras, P. (eds.) AI 2011. LNCS (LNAI), vol. 6657, pp. 110–121. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-21043-3_14
Tagliaferri, F., Philpott, A.B., Viola, I.M., Flay, R.G.J.: On risk attitude and optimal yacht racing tactics. J. Ocean Eng. (2014)
White, J.D.: A survey of applications of Markov decision processes. J. Oper. Res. Soc. JSTOR, 1073–1096 (1993)
Kerwin, J.E.: A Velocity Prediction Program for Ocean Racing Yachts. Massachusetts Institute of Technology, Department of Ocean Engineering (1978)
Shapley, L.S.: Stochastic games. Proc. Natl. Acad. Sci. USA 93(10), 1095 (1953)
Littman, M.L.: Markov games as a framework for multi-agent reinforcement learning. In: ICML 1994, pp. 157–163 (1994)
Matos, M., Cristina, P., Ferreira, M.A.M.: Game theory, the science of strategy. Int. J. Latest Trends Financ. Econ. Sci. 4(2), 738 (2014)
Roncin, K., Kobus, J.M.: Dynamic simulation of two sailing boats in match racing. Sports Eng. 7(3), 139–152 (2004)
Stelzer, R., Proll, T.: Autonomous sailboat navigation for short course racing. Robot. Auton. Syst. 56(7), 604–614 (2008)
Richards, P.J., Le Pelley, D.J., Jowett, D., Little, J., Detlefsen, O.: A wind tunnel study of the interaction between two sailing yachts. In: 21st Chesapeake Sailing Yacht Symposium, Annapolis, Maryland, pp. 162–168 (2013)
Richards, P.J., Aubin, N., Le Pelley, D.J.: The interaction between sailing yachts in fleet and match racing situations. In: 23rd International HISWA Symposium, Amsterdam (2014)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Belaouer, L., Boussard, M., Bot, P., Claramunt, C. (2020). A Non-cooperative Game Approach for the Dynamic Modeling of a Sailing Match Race. In: Di Martino, S., Fang, Z., Li, KJ. (eds) Web and Wireless Geographical Information Systems. W2GIS 2020. Lecture Notes in Computer Science(), vol 12473. Springer, Cham. https://doi.org/10.1007/978-3-030-60952-8_20
Download citation
DOI: https://doi.org/10.1007/978-3-030-60952-8_20
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-60951-1
Online ISBN: 978-3-030-60952-8
eBook Packages: Computer ScienceComputer Science (R0)