Can a computer learn to sail an Optimist with AI?
Conference/JournalMARIN Report 139
Date29 mrt. 2024
Put a child in an Optimist and it will learn how to sail intuitively, without understanding the details of aerodynamics and hydrodynamics. This inspired MARIN’s AI Sail Team to take up a challenge: can a computer learn to do the same with the help of AI? November 2023 was the moment of truth, during a demonstration in our Offshore Basin.
The background of this challenge is an important one: what can artificial intelligence and machine learning contribute to a cleaner, smarter and safer maritime world? Most maritime prediction methods are founded on a model-based approach: physics-based models are combined in a computational model and validated in tests and reality. With AI Sail we want to demonstrate the possibilities of data-driven methods, where the physics are not explicit in the model, but implicit in the data.
The background of this challenge is an important one: what can artificial intelligence and machine learning contribute to a cleaner, smarter and safer maritime world? Most maritime prediction methods are founded on a model-based approach: physics-based models are combined in a computational model and validated in tests and reality. With AI Sail we want to demonstrate the possibilities of data-driven methods, where the physics are not explicit in the model, but implicit in the data.
Contact
Hannes Bogaert
President
Bart Mak
Senior Researcher
Fanny Rebiffe
Applied Data Scientist
Risky behaviour
Full control also means that risky behaviour can emerge. Without limiting the actions the AI can explore, undesirable behaviour can be avoided by giving proper feedback on this behaviour. This often requires the introduction of terms in the reward function that do not directly relate to the objective but serve as implicit instructions on what not to do.
Moment of truth - AI Sail demontration in our Offshore Basin
Demonstration in MARIN’s Offshore Basin
Tags
data sciencetime-domain simulationsai