Speciation of Population in Neuroevolutionary Ship Handling

• Autorzy: Lacki M.
• Języki publikacji: EN

Abstrakty

EN

This paper presents the idea of using machine learning techniques to simulate and demonstrate learning behavior in ship maneuvering. Simulated helmsman is treated as an individual in population, which through environmental sensing learns itself to navigate through restricted waters selecting an optimum trajectory. Learning phase of the task is to observe current situation and choose one of the available actions. The individual improves his fitness function with reaching destination and decreases its value for hitting an obstacle. Neuroevolutionary approach is used to solve this task. Speciation of population is proposed as a method to secure innovative solutions.

Słowa kluczowe

EN

Ship Handling; machine learning techniques; Restricted Waters; Neuroevolutionary Ship Handling; manoeuvering; Multi-Attribute Decision Making (MADM); Optimum Trajectory; Neuro Evolution of Augmenting Topologies (NEAT)

• Wydawca: Faculty of Navigation, Gdynia Maritime University
• Czasopismo: TransNav : International Journal on Marine Navigation and Safety of Sea Transportation
• Rocznik: 2010
• Tom: Vol. 4, no. 2
• Strony: 211--216
• Opis fizyczny: Bibliogr. 14 poz., rys., tab.

Twórcy

autor

Lacki M.

• Gdynia Maritime University, Gdynia, Poland

Bibliografia

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