| CPC G06F 11/3442 (2013.01) [G06F 9/505 (2013.01)] | 20 Claims |

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1. A method, comprising:
identifying, by a system comprising a processor, a first capacity associated with completion of first tasks of a first task type;
identifying, by the system, collected production data representing a result of a workflow executed by a first worker resource of a plurality of worker resources having a plurality of tasks of a plurality of task types, wherein each of the plurality of tasks are associated with different capability and capacity;
generating a first training data set from the collected production data, wherein the first training data set comprises a first pseudorandom selection of the collected production data;
training, by the system, using the first capacity associated with completion of first tasks of a first task type and the first training data set, an artificial neural network (ANN) to predict resource capacities of the plurality of worker resources;
receiving, by the system, from the ANN, a prediction that the first worker resource has the first capacity;
generating a second training data set from the collected production data, wherein the second training data set comprises a second pseudorandom selection of the collected production data; and
providing subsequent training of the ANN using the second training data set.
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