Abstract: A technique for learning and steering evolutionary dynamics may include initializing a bioreactor including a population of evolving organisms; determining selection pressures; (a) applying the selection pressures to the population; (b) determining the population state and storing it in a population dataset; (c) detecting whether the population has reached a stable state; (d) if the population has reached the stable state: obtaining data representing the stable state, redetermining the selection pressures based on a selection pressure policy, and storing the data and the redetermined selection pressures in a stable state dataset; (e) determining whether one or more stopping criteria have been met; and repeating steps (a)-(e) until at least one of the stopping criteria is met.

Abstract: A bioreactor system can include one or more bioreactor groups, where each group has a plurality of bioreactor clusters and a gantry shared by the plurality of bioreactor clusters. Each bioreactor cluster can include one or more manifolds and a plurality of bioreactor units. Each bioreactor unit can include a well, a lid covering the well, a waste valve to control a flow rate of waste out of the well, and one or more dispensing valves to control flow rates of dispensing one or more materials into the well. The gantry can include one or more sensors and a movable gantry head with one or more sensor probes configured to selectively sense properties of contents of respective bioreactor units included in the plurality of bioreactor units.

Abstract: A technique for learning and steering evolutionary dynamics may include initializing a bioreactor including a population of evolving organisms; determining selection pressures; (a) applying the selection pressures to the population; (b) determining the population state and storing it in a population dataset; (c) detecting whether the population has reached a stable state; (d) if the population has reached the stable state: obtaining data representing the stable state, redetermining the selection pressures based on a selection pressure policy, and storing the data and the redetermined selection pressures in a stable state dataset; (e) determining whether one or more stopping criteria have been met; and repeating steps (a)-(e) until at least one of the stopping criteria is met.