The Mind Grows Circuits

TL;DR

This paper proposes a model where the mind develops complex circuits incrementally from primitive components, using repeated experiences to form new nodes, aiming to compress sensory input and understand cognitive growth.

Contribution

It introduces a novel circuit growth model based on composition of primitive components driven by experience, differing from neural networks by handling concepts as inputs and outputs.

Findings

Circuits grow incrementally through experience-based composition.

The model aims to compress sensory input to reduce Kolmogorov Complexity.

Provides a new perspective on cognitive development as circuit growth.

Abstract

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.