1. A probabilistic learning element that sequentially receives objects and outputs sequences of recognized states, said learning element comprising: means for sequentially receiving objects; means for storing received object information, including, said received objects, and sequences of received objects; means for storing items of previously learned information, said items including, sequences of states, states contained in said sequences of states, objects contained in said states contained in said sequences of states, sequences of objects contained in said states contained in said sequences of states, positional information for each object contained in said states contained in said sequences of states, and predetermined types of knowledge relating to said previously learned information, whereby received object information, relating to received objects, is stored as well as previously learned information; means for correlating said received object information with said previously learned information for assigning conditional probabilities to possible sequencies of recognized states; means, responsive to said conditional probabilities of possible sequences of recognized states, for determining a most likely sequence of recognized states; means, responsive to said previously learned information, for detecting that a state has ended and for providing an end of state signal; and means, responsive to said end-of-state signal, for outputting said most likely sequence of recognized states as a recognized state sequence.