Towards a theory of everything
Copyright 2016 Graham Berrisford.
One of about 300 papers at http://avancier.website. Last updated 09/01/2017 14:50
The aim here is not to present a new “a priori” view of the world.
The aim is to present a coherent and consistent view of the world, compatible with the evolution of animals, society, business and software.
A side effect of telling this story is the drawing of relationships between various theories related to system architecture.
This paper is only taster: the theories mentioned below are explained in other papers.
Philosophy and description theory
The survival of intelligent actors depends on their ability to create and use descriptions of reality.
Realist philosophers say realities have descriptions, which describers can discover.
Idealist philosophers say describers create descriptions to help them deal with realities.
Our practical idealism separates describers, descriptions and described realities.
<create and use> <idealise>
Describers <observe and envisage> Realities
Note that most realities are more complex and multi-faceted than any description of them.
And that a particular reality may not exactly fit a description applied to it.
Outside of mathematics and computing, fuzzy matching of realities to descriptions is normal.
Social systems depend on actors sharing meanings encoded in signals they send and receive.
Claude Shannon developed “information theory” about the limits on signal processing operations such as compressing, storing and communicating data.
But as long ago as 1956, Boulding observed that Shannon did not address the meaning of communication in social and business systems.
For us, the fundamental problem of communication is that of knowing what a message means, at a logical level.
Enterprise architecture seeks to integrate business systems that maintain data stores (memories) and exchange data flows (messages).
To create and find logical information in those data flows and data stores, actors must agree what information/meanings they contain.
Set and type theories
A set can be defined by extension: by enumerating the members of the set (e.g. by listing the colours of the rainbow, or even numbers).
Mathematicians see a set as static in the sense that it cannot gain or lose members.
However, other disciplines speak of “sets” when talking about collections of things that are dynamic.
The members of a dynamic set are better defined by intension: by typify a set member, listing properties shared by instances of the type.
Linguistics and fuzzy logic
Evolution led to human-level self-awareness and verbalisation, to the use of words to describe things of interest.
Our descriptions use words to typify particular things as instances of conceptual types.
All verbal types are logical abstractions, they are constructs of intelligence.
But note that that most are fuzzy, not the strict types of mathematics and computing.
General system theory is about features common to mechanical, biological and social systems.
Business systems are formalised social systems, in which actors cooperate in activities by exchanging information.
System architects describe systems in terms of actors/components (structure) and activities/processes (behaviour).
These formalised social systems, aka business capabilities, are designed and changed under change control.
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