1. A machine learning system having a plurality of agents, the system comprising: a model manager for providing a model to the plurality of agents, the model specifying attributes and attribute value data types for an event in which the plurality of agents act; an agent input sub-system for receiving agent-provided inputs from the plurality of agents during an instance of the event, the agent-provided inputs include estimated attribute values that are consistent with the attribute value data types; a ground-truth-based expertise weighting determiner having a processor for determining expertise weights for at least some the plurality of agents in response to at least one ground-truth which is learned from the estimated attribute values; and an adaptive attribute value mixer for determining an estimate value for one or more of the attributes using respective adaptive mixtures of the estimated attribute values.