Machine Learning and Instrument Autonomy Group

Principal Investigator

Lukas Mandrake

The Tuning Optimizing Genetic Algorithm (TOGA) was developed on the Ocean Worlds Life Surveyor project to perform black-box optimization on software with large numbers of tunable parameters. In addition to featuring highly configurable and transparent mutators, crossover functions, population controls, and performance metrics, TOGA is able to take full advantage of high performance distributed computing with its client-server architecture for fast convergence. TOGA provides optimization for both classifier selection and hyperparameter tuning, in addition to supporting sensitivity studies and tradeoff analysis between configuration options.

Please visit our public GitHub repository for more information.