Axiomatic Theories of Intentional Systems (ATIS)

ATIS  provides the means to predict system outcomes of intentional systems under two conditions:  

  • System Axiomatic Predictions, and
  • Anticipatory Predictions.  

Initially, it is the System Structural Predictions that are of greatest concern since these can be obtained with great
precision due to the axiomatic theory utilized.    

ATIS  is a "formal theory."  That is, it utilizes logico-mathematical concepts to accurately develop its own language and
is designed to provide a rigorous explication of the theory.  With the latest developments, ATIS is now a mathematical
theory.  

Further, it is an axiomatic theory.  To date, axiomatic theories are the only ones that provide for rigorous analysis and
outcomes that can be relied upon with confidence.  

Discussed below is an introduction to axiomatic predictions and anticipatory predictions.  
A-GSBT (Axiomatic-General Systems
Behavioral Theory)  has been changed
to ATIS  (Axiomatic Theories of
Intentional Systems)

And, Raven58 Technologies has
been maintained as the parent business,
but we are now doing business as:  

System-Predictive Technologies.  


"Axiomatic Theories of Intentional
Systems" more accurately describes the
theory, and System-Predictive
Technologies more accurately
describes what we do as a result of the
theory.  

-- Ken Thompson, Head Researcher/
Owner Raven58 Technologies, dba
System-Predictive Technologies
                                                
System Axiomatic Predictions

System Axiomatic Predictions are those predictions that can be made as a direct result of the system-
descriptive axiom set.  These are predictions that result in complete accuracy since the alternative
would be contrary to the underlying axioms.  For example, imposing strategic paralysis is a System
Axiomatic Prediction, since the outcome is absolutely certain.  As will be considered later, any result
obtained directly from the axioms is a System Axiomatic Prediction, since any alternative outcome
would contradict the axioms.  

In a broader context, this predictive strategy is distinctly different from the data-mining strategies that
attempt to extract structure from an unstructured database.  As an alternative, we have the ATIS
System Axiomatic Prediction Principle:  

  • ATIS provides the system structure into which new data is integrated, and thereby gives rise to
    new structure that compels the recognition of a resulting action as determined by the new
    system parameters that if not produced would be inconsistent with ATIS axioms.  

Stated another way, structure determines possible and intended system action:  

  • System Structure compels the recognition of intended action determined by system parameters
    that if not produced would be inconsistent with ATIS principles.  

  • Each new introduction of affect relations into a system defines an Induced System Structure
    that compels recognition of new intended action.  




System Anticipatory Predictions

Another type of prediction with which we are concerned will be identified as Anticipatory Predictions.  
There are no claims that such predictions will be 100% accurate when empirically tested.  But, an
Anticipatory Prediction will be considered to have been validated if the outcome is either accurate, is
accurate within acceptable well-defined tolerances, or can be explained by changes that occurred
between the time the system structure was evaluated and the outcome was observed.  

In fact, Anticipatory Predictions account for “changed intentions.”   That is, an outcome that is
contradictory to that predicted but was obtained as the result of “changed intentions” remains an
accurate outcome if, in particular, the actual outcome would have resulted had the changed intentions
been known.  

The premise of ATIS is that total system structure will provide the most accurate predictive capability.  
Further, predictability is not the result of system dispositional behavior, nor the result of any statistical
inference obtained from prior behavior.  Dispositional behavior and prior states provide an invariant
structural base against which to analyze current data, but do not result in behavior predictability.  
Anything other would result in a deterministic or mechanistic type system, rather than the dynamic
teleological type system here contemplated.  

Further, the system structure provides a basis for analysis, but the resulting behavior prediction is a
result of a logical as well as topological analysis, it is not simply the result of a single algorithm derived
from a logical schema, or a single topological analysis derived from the affect relations.  
System-Predictive Technologies' (Raven58 Technologies') primary R&D
project is developing and extending ATIS (A-GSBT)  to various applications
where system behavior is a primary factor in predicting outcomes, whether
business productivity outcomes, terrorist activity outcomes, learning outcomes,
job performance outcomes, or other outcomes founded on behavioral properties.



SIGGS Theory provided the initial foundations for the development of A-GSBT.
The research of System-Predictive Technologies is indebted to Elizabeth
Steiner and George Maccia for the work accomplished at the Educational Theory
Center, The Ohio State University, from 1964 to 1966.  Further, the work of
Theodore Frick, Indiana University, in the 1990's provided the refinements of the
earlier theory that led to the current development of ATIS (A-GSBT).  
ATIS INTRODUCTION