1. A method comprising: controlling operation of a semiconductor manufacturing system with a state machine and generating, with the state machine, at least in part a schedule for processing of one or more workpieces, the state machine including a plurality of states associated with a plurality of transitions, each one of the plurality of transitions having a weight assigned thereto and each state corresponds to a workpiece processing function of a piece of equipment of the semiconductor manufacturing system, the semiconductor manufacturing system including at least two workpiece handling robots in at least two processing planes, the robots capable of handing workpieces between the at least two planes; receiving data from the semiconductor manufacturing system; calculating the weight assigned to each one of a number of possible transitions from a current state of the plurality of states for a predetermined piece of equipment of the semiconductor manufacturing system by applying the data as inputs to a neural network; and selecting a transition of the workpiece processing function of the predetermined piece of equipment to a second state from the current state of the plurality of states by evaluating the weight assigned to each one of the number of possible transitions from the current state, wherein the state machine sends control signals to the semiconductor manufacturing system and control processing that re-evaluates or reconfigures the state machine is separated from operation of the state machine such that the state machine operates to send the control signals independent of the neural network to provide transitions among states according to inputs from the semiconductor manufacturing system.