Monthly Archives: November 2013

What are Complexity Sciences?

The objective of the Unicist Approach to Complexity Sciences developed by Peter Belohlavek was to find a scientific approach to understand nature and provide a structure to emulate it when designing, building or managing complex adaptive systems.

Unicist Approach to Complexity SciencesBelohlavek developed the epistemological structure for complexity sciences, by developing the unicist ontological methodology for complex systems research, which substituted the systemic approach to research adaptive systems and was materialized in the unicist logical approach to deal with adaptiveness.

This is an excerpt comparing the different approaches that intended to deal with Complexity Sciences. It needs to be stated that the unicist approach developed the first integrated structure to manage complex adaptive systems.

Until the existence of this approach the methods of systemic sciences were used as a palliative to deal with complex adaptive behaviors.

The structure of the unicist approach to complexity sciences implies the integration of a unicist ontological approach, which defines the structure of the nature of a specific reality with the use of unicist objects that allow emulating the organization of nature to predict the behavior of complex adaptive systems, design them, built them or manage them.

Access to a synthetic comparison of the Unicist Approach with the different approaches based on their nature and functionality:

  1. Complex Adaptive Systems
  2. Ontologies
  3. Objects

Comparison of the Approaches to Complexity Sciences


Peter Belohlavek’s approach
to Complexity Sciences

Preexisting approaches: Bateson, Förster, Lorenz, Maturana, Morin, Prigogine
and others

Field of Study Complex adaptive systems Complex adaptive systems
Approach Pragmatic – Structural – Functionalist Empirical
Definition of the field of study A specific reality as a unified field that includes the restricted and wide contexts and the emergence of the system Based on the emergence of the system
Possibility of external observation Inexistent Inexistent
Research method Unicist Ontological Research Systemic research
Boundaries of the system Open Open
Self organization Concepts – analogous to strange attractors Strange Attractors / undefined
Structure Double Dialectics Dynamics
Purpose – active function – energy conservation function
Relationship between the elements Following complementation and supplementation laws Undefined
Evolution / Involution Based on the evolution/involution laws of the ontogenetic intelligence of nature Undefined
Processes Object driven processes Undefined
Certainty Dealing with possibilities and probabilities Dealing with probabilities
Demonstration Real applications Real applications
Emulation in mind Double dialectical thinking
(using ontointelligence)
Complex thought
Emergence Results Results
Chaos Inexistent Existent
Influence on the system Based on actions and driving, inhibiting, entropy inhibiting, catalyzing and gravitational objects. Based on actions
Validation Destructive and non-destructive tests (real applications) Systemic research validation methods


Comparison of Ontologies with the Unicist Ontology

Comparison of:

Ontology (Philosophy)
Aristotle, Wolff,
Kant and others

Ontology (Information Science)
Gruber, Sowa, Arvidsson and others

Unicist Ontology (Complexity Sciences)
Peter Belohlavek (*)

Purpose Knowledge acquisition Information and knowledge acquisition Managing complex adaptive systems and adaptive processes
Foundations Discovery Shared expert opinions Ontogenetic Intelligence of Nature and discovery of functionalities
Use in business To apprehend reality Artificial Intelligence  and building of complex information systems Manage human adaptive systems and adaptive processes
Scope of application Universal Artificial Intelligence, Information Systems Development of ontogenetic maps for the individual, institutional, business and social fields.
Language used Natural Web Ontology Language and others Unicist Standard Language and natural language
Results to be achieved True knowledge Valid knowledge and information Value generation
Evolution / Involution laws Inexistent Inexistent Unicist laws of evolution
Validation model Inexistent Inexistent Unicist logic
Taxonomic structure Inexistent Based on shared validation Defined by the Unicist Algorithms
Mathematic validation Inexistent Inexistent Following the Unicist logic
Deals with Ideas Categories and objects Algorithms and business objects
Oneness One ontology for each aspect of reality Depending on the consensus of the expert opinions One ontology for each functionality

Comparison of the different types of objects

Objects Oriented Programming

Main concepts of objects in IT programming

Complex Adaptive

Main concepts of
unicist objects

Adaptive Systems
in Nature

Main concepts of objects in nature (e.g. a tree)

Class Restricted Context Species
Object Business Object Entity
Inheritance Homologous Inheritance Inheritance
Method Method Functionality
Event Action Action
Message Information System Nervous System
Attributes Fundamentals Morphology
Abstraction Ontogenetic Map Genotype
Encapsulation Unified Field Phenotype
Polymorphism Polymorphism Polymorphism
Synchronicity Synchronicity
Critical Mass Critical Mass

Complexity Science Research

The unicist theory expanded the frontiers of sciences making the scientific approach to complex adaptive systems possible without needing to use arbitrary palliatives to transform complex systems into systemic systems in order to be able to research them.

Complexity Science ResearchParadoxically, this is a breakthrough and a back to basics. On the one hand, it is a breakthrough because it changed the paradigms of scientific research. On the other hand, it is a back to basics because it drives sciences to deal with the nature of reality.

The unicist logical approach opened the possibilities of managing complexity sciences using a pragmatic, structured and functionalist approach.

The unicist approach to complexity is based on the research of the unicist ontological structure of a complex adaptive system which regulates its evolution. This is based on emulating the structure of the unicist ontogenetic intelligence of nature considering that every functional aspect of reality has a unique unicist ontological structure.

The approach to ontological structures of reality requires going beyond the dualistic thinking approach and being able to use the double dialectical logic to approach complex adaptive systems.

The research in complexity science needs to have its own format for its presentation that has a structural difference with the papers for systemic sciences (abstract, introduction, materials and methods, discussion, literature).


The unicist approach to complexity sciences is a pragmatic, structural and functionalist approach.

This approach establishes the framework for the research on complexity sciences but also for the unicist logical approach that uses the conclusion of the researches in their application in the field of complex adaptive systems.

The Unicist Research Institute

NOTE: The Unicist Research Institute was the pioneer in complexity science research and became a private global decentralized leading research organization in the field of human adaptive systems.