Iterative Dialectic Engine for Automated Learning

What led to IDEAL?

IDEAL is the result of much thought on a variety of subjects over many years.  Since 1995 these thoughts have been written down in order to engage the process of iterative development.  To date this has resulted in 7 kg handwritten notes and IDEAL.  The main themes of this research are:

  1. The process of iterative development;

  2. General principles and particular instances;

  3. Dialectic reasoning;

  4. Scientific method;

  5. The distinction between data and control;

  6. Human consciousness.

This research establishes the following conditions for any design of an automated learning engine:

  1. It must be based on the process of iterative development;

  2. It must be able to distinguish general principles and particular instances, and it must be able to compare and correlate input data and stored data;

  3. It must be able to reconcile opposing opinions or facts, by whatever means;

  4. It must be able to manipulate an ensemble of scenarios generated using a toolbox of models;

  5. It must be able to distinguish between data and control;

  6. It must be able to express and record the relative importance of input data and stored data.

To design the automated learning engine we implement these conditions in a flowchart.  Condition 5 calls for two types of connector:

Data connector.

Control connector.

Condition 2 calls for a distinction between general principles and particular instances.  These comprise the stuff of algorithms and input/stored data devices respectively:


Algorithm component.  The configuration of connectors is based on the transistor (i.e. emitter, base and collector).

Evidence component, for input data.
Log component, when storing data.
Log component, when retrieving data.  Note that, in this mode, L's functionality is identical to E's.

Conditions 2 and 3 call for the comparison, correlation and reconciliation of data:

Iteration component.  Typically this flowchart symbol is used:  (i) to indicate the start of an iteration loop;  (ii) to define the initial parameter values for the iteration; (iii) to apply iteration completion conditions.  The last of these functions involves data comparison, as required.

Condition 4 calls for the facility to manipulate a number of scenarios and models.  To do this, L must contain descriptions (e.g. source code) of all of the system algorithms, and there must be a central decision component.  Condition 6 calls for the ability to modify input/stored data, which also requires a decision component (in addition to A, E and L, already defined):

Decision component.

Finally, Condition 1 calls for an implementation of the process of iterative development.  The simplest iterative configuration involving all of the required components is IDEAL:


The Activist:  "Very interesting... but What next for IDEAL?"

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Copyright Roger Kingdon 2004