A real-time strategy-decision program for sailing yacht races

Optimal decisions for a skipper competing in a match race depend on a number of factors, including wind speed and direction variations, behaviour of the opponent, sea state, currents, racing rules. Expert sailors are able to combine observations on these various factors and process them to take optimal decisions. This study presents an attempt at emulating this decision process through a computer code that can be used in real time to advise on race strategy. The novelty of the proposed method consists in combining various approaches for the multiple factors affecting the decision process. The wind variability is modelled with the use of neural networks, to produce a short-term wind forecast. The willingness of the sailor to risk is modelled using coherent-risk measures. Experimental results are used to quantify the loss of speed due to the presence of a nearby opponent. Finally, all these factors are combined through dynamic programming to compute an optimal course, based also on information on the current and yachts performance. The program is tested modelling the last 13 races of the 34th America's Cup, and results show that the route computed is close to the shortest possible route computed assuming perfect knowledge of

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