Our main objective is to research ATL schemes and techniques to be applied to the modeling of ocean processes. The specific goals will be to:
- Research, apply and implement learning theory and principles to ocean modeling
- Develop idealized and realistic ocean modeling tests beds for ATL research
- Incubate new (machine) learning schemes based on the idealized set-ups and test the best ones in realistic simulations.
- Provide ocean data, simulations, software and methodology to the ATL project research teams
- Collaborate and transfer of expertise, approaches, algorithms and software to and from naval laboratories and centers.
- ATL directly from ocean measurements (either simulated or real): learning science/processes from data alone
- ATL within realistic complex simulations (as complex as real-ocean)
- Science challenge: find new processes in these complex simulations
- Naval challenge: what are the keys for the Naval operator
- ATL from mismatch between models and measurements
There are three types of ATL learning applications and scenarios that we plan to research using realistic ocean simulations and idealized simulations: