Agent based match racing simulations: Starting practice
Paper in proceeding, 2022

Match racing starts in sailing are strategically complex and of great importance for the outcome of a race. With the return of the America's Cup to upwind starts and the World Match Racing Tour attracting young and development sailors, the tactical skills necessary to master the starts could be trained and learned by means of computer simulations to assess a large range of approaches to the starting box. This project used game theory to model the start of a match race, intending to develop and study strategies using Monte-Carlo tree search to estimate the utility of a player's potential moves throughout a race. Strategies that utilised the utility estimated in different ways were defined and tested against each other through means of simulation and with an expert advice on match racing start strategy from a sailor's perspective. The results show that the strategies that put greater emphasis on what the opponent might do, perform better than those that did not. It is concluded that Monte-Carlo tree search can provide a basis for decision making in match races and that it has potential for further use.

Author

D. Lidstrom

Student at Chalmers

Torbjörn Lundh

Chalmers, Mathematical Sciences, Applied Mathematics and Statistics

Laura Marimon Giovannetti

SSPA Sweden AB

SNAME 24th Chesapeake Sailing Yacht Symposium, CSYS 2022

SNAME 24th Chesapeake Sailing Yacht Symposium, CSYS 2022
Annapolis, USA,

Subject Categories

Bioinformatics (Computational Biology)

Software Engineering

Information Science

DOI

10.5957/CSYS-2022-009

More information

Latest update

8/5/2022 1