[This is a work in progress. This page is not meant to explain anything. It’s only meant to put all the moving parts in one place.]
The most fundamental things we can know about are processes. We can only identify or know about things by the processes they participate in.
Most processes can be diagramed as Input->[System]->Output. We say the System causes the Output when presented with the Input.
The main feature of information is correlation, aka mutual information. All processes cause correlation, and thus, all processes cause information.
Some systems which, by their organization, tend to move the environment toward a particular state. These systems have been described as self-organizing, or cybernetic, or goal-oriented. Natural selection describes such a system.
5. Final causation
Some systems create new subsystems, which subsystems contribute to the goal of the creating system. Such subsystems can be said to have the goal of moving the environment toward the goal state associated with the original system. Aristotle’s final cause refers to this goal.
Representation is a combination of (at least) two processes. The first process creates a sign vehicle whose goal (purpose) is to carry mutual information. The second process takes that vehicle as input and generates a response which is valuable w/r to the goal. (See the diagram in the page banner).
Some systems will find multiple pathways to achieve a goal, and will therefore create multiple subsystems with different sub goals. Eg., one subsystem to find food and another to avoid predators. Sometimes the goals conflict, as when there is a leopard in the fig tree. An agent is a system which has a subsystem which solves conflicts between sub goals based on internal representations.
8. Pattern recognition (unitrackers)
A unitracker is a computational mechanism which looks for one target pattern given some number of inputs. The output of a unitracker is a sign vehicle (an affordance of representation) which carries mutual information with respect to the unitracker mechanism, and so too, to the target pattern of the unitracker.
9. Multi-pattern Medium
A multi-pattern medium is a mechanism that can take inputs from one or more sources and generate a pattern of output which is unique to each combination of sources. The paradigm sources for purposes of this theory would be unitrackers. A semantic pointer (ala Chris Eliasmith) is an example.