1. A computer-implemented method for predictive decision-making, comprising: receiving a set of rules into an ad-hoc network having distributed nodes, wherein each distributed node is capable of processing data as a function of one or more rules in the set of rules; identifying a respective data set including data that is a respective potential candidate for each rule of the received set of rules; selecting a first node from the distributed nodes configured to identify candidate data and disregard non-candidate data received by the first node for a first rule of the received set of rules as a function of the identified respective data set for the first rule; selecting a second node from the distributed nodes configured to identify candidate data, and disregard non-candidate data, received by the second node for a second rule of the received set of rules as a function of the identified respective data set for the second rule; selecting a third node from the distributed nodes configured to receive identified candidate data from each of the first and second nodes and to index the received candidate data in memory by its spatial, temporal, or contextual elements as a function of the received set of rules; receiving identified candidate data from each of the first and second nodes at the third node; indexing the received candidate data in memory at the third node by its spatial, temporal, or contextual elements as a function of the received set of rules; and providing an indication of the indexed candidate data at the third node.