The importance of human factors has to be taken into account when determining a yacht’s performance over a course. The crew’s capabilities of technical skills, athletic performance, and his/her ability of making rational decisions under time pressure and in light of uncertainty of the future wind regime are important aspects that will determine the overall performance of a yacht-crew system. This thesis highlights the performance of such a yacht-crew system with a focus on the decision-making process of sailors. Aspects of human behaviour in sport and the decision-making process are explained considering the level of expertise and possible approaches of how to model them are shown. An artificial intelligence AI -system is developed that is capable of simulating the decision-making process of different sailing behaviours/styles as well as different expertise levels of sailors within a dynamically changing yacht racing environment. The constraints of the multiple fleet racing simulator Robo-Race (Scarponi 2008) were determined using a series of tests with real sailors identified three important constrains: (1) the predictable behaviour of the AI-yachts, (2) the predictable and unrealistic weather model and (3) the simple model describing the effects of yacht interaction. These restrictions and constraints that limited the real and AI-sailors natural sailing behaviour have been successfully removed in the updated version of Robo-Race. The new developed decision-making engine based on Decision Field Theory that uses Bayesian Belief Networks as the perceptual processor showed a clear superiority over the old rule-based decision-making engine. Extensive simulations demonstrate the feasibility of modelling various decision-making processes and therefore different behaviours and expertise levels of sailors. A good comparison was found with that obtained between the Robo-Race results and the Olympic fleet racing events.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:628717 |
| Date | January 2014 |
| Creators | Spenkuch, Thomas |
| Contributors | Hudson, Dominic |
| Publisher | University of Southampton |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | https://eprints.soton.ac.uk/366587/ |
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