This paper presents Mona, a connectionist model of motivation implemented by a network of neuron-like components whose interactions drive behavior toward goals which reduce homeostatic needs. The network incorporates a short term memory capability allowing it to model a state-space with relatively few neurons.

A technique for creating and searching a tree of patterns using relative distances is presented. The search is conducted to find patterns which are nearest neighbors of a given test pattern. The structure of the tree is such that the search time is proportional to the distance between the test pattern and its nearest neighbor, which suggests the anomalous possibility that a larger tree, which can be expected on average to contain closer neighbors, can be searched faster than a smaller tree. The technique has been used to recognize OCR digit samples derived from NIST data at an accuracy rate of 97% using a tree of 7,000 patterns.>