  There is a vast supply of prior art that study models for mental processes.
Some studies in psychology and philosophy approach it from an inner perspective
in terms of experiences and percepts. Others such as neurobiology or
connectionist-machines approach it externally by viewing the mind as complex
circuit of neurons where each neuron is a primitive binary circuit. In this
paper, we also model the mind as a place where a circuit grows, starting as a
collection of primitive components at birth and then builds up incrementally in
a bottom up fashion. A new node is formed by a simple composition of prior
nodes when we undergo a repeated experience that can be described by that
composition. Unlike neural networks, however, these circuits take "concepts" or
"percepts" as inputs and outputs. Thus the growing circuits can be likened to a
growing collection of lambda expressions that are built on top of one another
in an attempt to compress the sensory input as a heuristic to bound its
Kolmogorov Complexity.
