Abstract: Circuits, devices and methods for processing learning networks are implemented using a variety of methods and devices. One example involves a circuit-implemented method to identify a relationship of objects in a set of objects. Local scores are generated for the object and possible parents. The local scores indicate relationship strength between object and parent. The results are stored in a memory. A state-machine circuit is used to perform sampling and searching of the parent sets for each data node. The local scores are used to encode orderings of the parent. An algorithm is executed that uses the encoded possible orderings and a random variable to generate and score a current order and a proposed order of the possible parent sets. The proposed orders are accepted or rejected based on probability rules applied to the scores for the current and proposed orders. Structures are sampled to assess a Bayesian-based relationship.