Strain design optimization using reinforcement learning
Fig 1
Strain design optimization loop using reinforcement learning.
Enzyme levels corresponding to the strain i are denoted as ei, and yi and si, correspond to the response (used in reward) and output concentrations (used as state), respectively. The action (ai), corresponding to the difference of the enzyme levels in the two consecutive iterations, is given by the policy learned with MMR.