If the brain were a car engine, what kind of gears would it contain? What is the structure of repeated forms of the cortex, that house the algorithms of human cognition?

My research stems from the desire to understand animal thought as a network of repeated forms, as the brain is made of the repeated forms of nerves or mini columns, or a motor is made of gears and other things. This site describes the resulting cognitive architecture, used for constructing robotics controllers, also known as brains. The approach used is constructive -- a set of atomic forms is defined and networks of them which work well identified. These sweet spots have the learning abilities described by Piaget, such as assimilation.

These brains are constructed from a repeated form called a "factals". Each atomic form can represent one fact about the world, which at any moment may be either true or false, and/or may be wanted or not. A factal represents its 1-bit of information about the world in all of the brains calculations, in it's thought processes. The site describes how layers of factals are connected, each only to nearby factals (as do nerves or gears). The research seeks to build up larger and larger machines, with greater and greater capabilities.  The hierarchically compose-able schema it produces creates associations that are the basis for remembering and imagining.

The first phase is to define appropriate mechanisms, the second step is to refine these mechanisms with computer simulation, and the third step is to locate the sweet spots from which the emergent properties of animal thought arise. 


The Factal Workbench is the results of generations of refinements, as the design was reformulated over a decade or more. The entries below start with the latest most concise formulation of the mechanism.  Later entries give the big picture, leading to them.
  • WARNING: You are about to "drink from a firehose". The trick is not to drink too much at a time, but to keep going back for more. If you get 10% each time, you're doing good. Any suggestions that help the next reader are solicited.
1. 2016 Biological Inspired Cognitive Architectures 2016 

The simulation videos for the paper to be presented at BICA16 (July 16, 2016 in New York City) 

2. 2015 The Factal Workbench 2.0

This  shows the operation of several HaveNWant machines, in a series of short videos made from screen shots of the latest release. Watch videos of the Factal Workbench in operation, and to gain an intuitive understanding of how the elements of various small machines operate together.

3. 2014 The HaveNWant Schemata

The HaveNWant Schemata describes how a particular set of one-bit parts can be connected with rules to perform some cognitive learning tasks described by Piaget. It is the description of a specific causal mechanism. Read more about HaveNWant Schemata, and see the presentation made at the Biologically Inspired Cognitive Architectures at MIT 11/14.

4. 2013 Application Areas

How might the HaveNWant Schema be used to do some higher level tasks. It contains 4 short papers, including one on Language Deserialization (how to implement language in HaveNWant Reenactment Simulator), and on Bindings (how to ground symbols in sensations).

5. 2013 Yaagil and Yiav

This describes my best guess for the “Equation of Intelligence", presented informally in back rooms at Artificial Generic Intelligence Conference (AGI-12) in Oxford, England.  It describes how to build control structures out of 1-bit hierarchical bidirectional forms, and lead to the HaveNWant paper. Read more about Yaagil and Yiav, and delve into various aspects of how they might be deployed.

6. 2012 The Grandmother Turtle Schemata

A snapshot description of a cognitive schema that lead to Yaagil and YIAV, including how it makes associations, and simulates the future. Read the Grandmother Turtle paper.

This is an earlier paper that was presented at the memorial conference of a long-time friend Ray Solomonoff. This was in November 2011in Melbourne. The paper was also presented at the 24th Australasian Joint Conference on Artificial Intelligence (although it is not in the program). Read and watch the Design of a Conscious Machine

8. 2011 IEEE Robotics Group Talk

The first public presentation of thes ideas, on Tuesday February 8.  It covers much of the early motivations. Read more about IEEE Robotics Group Talk

9. 2010 Simple Connectionist Mechanisms of Cognition

A 70-page pdf manuscript, which defines facts and how they act in a semantic network to form forward models in a Reenactment Simulator. Read more about Simple Connectionist Mechanisms of Cognition

10. 2009 Hebbian Arborization

Describes a theoretical method by which nerves may grow to perform Hebbian networks.
Growing sparse Hebbian networks. (2 pages) Read more about Hebbian Arborization

11. 2008 Earlier Works

Available upon request.

  • This is a huge effort, and anybody who wants to learn more or help is encouraged to do so. Contact me if you'd like to discuss anything.