Agents

We define “agent” as an encapsulation of the machine learning algorithm. An ML algorithm consists of “hyperparameters” and a guiding “policy”. We currently support the following agents:

• Ant Colony Optimization (ACO)

• Genetic Algorithm (GA)

• Bayesian Optimization (BO)

• Reinforcement Learning (RL)

• Random Walker (RW)

• Vizier Algorithms

  1. Random Search (RANDOM_SEARCH): Flat Search Spaces.

  2. Quasi-Random Search (QUASI_RANDOM_SEARCH): Flat Search Spaces.

  3. Grid Search (GRID_SEARCH): Flat Search Spaces.

  4. Emukit Bayesian Optimization (EMUKIT_GP_EI): Flat Search Spaces.

  5. NSGA2 (NSGA2) : Flat Search Spaces.