Abstract: An apparatus for categorizing objects employs a neural network having a plurality of cells each having memory for storing a state variable, and a plurality of synaptic junctions connecting cells of the network and having memory for storing a synaptic strength variable. A computer is used to modify the synaptic strength variable in accordance with a heterocellular synaptic modification rule. That modification rule includes both the passage of time and the values of the state variables of each cell and of those other cells having specific spatial locations with respect to the cell in three dimensional space.

Abstract: An apparatus capable of sensing the presence of objects in its environment, categorizing these objects without a prior description of the categories to be expected, and controlling robotic effector mechanisms to respond differentially to such objects according to their categories. Such responses include sorting objects, rejecting objects of certain types, and detecting novel or deviant objects. The invention includes a device called a "classification n-tuple" (of which a "classification couple" is a special case) capable of combining signals from two or more sensory modalities to arrive at the classification of the object.The invention operates by simulating certain features of animal nervous system, including neurons with responses determined at each moment of time by inputs received along synaptic connections from sensory means or form other neurons. In this invention, neurons are arranged in "groups", which permits them to act cooperatively while still retaining characteristic individual responses.