Complexity Sciences Research


Complex problem solving requires dealing with superior ethical intelligence

The discovery of ethical intelligence unveiled the drivers of human behavior and widened the possibilities of individuals to manage their own future. Ethical intelligence defines how people generate added value, influence the environment, manage time, build strategies and focus on reality.

Ethical IntelligenceThis discovery is the major and deepest discovery in the field of human intelligence made by Peter Belohlavek.

Ethical intelligence provides the structural logic to survive, earn value, add value, acquire and manage knowledge and deal with the nature of reality. It is the “mother” of all the intelligences. It defines the true intentions of individuals that are observable in the consequences of their actions.

The higher the level of ethics an individual wants to achieve, the higher the prices s/he has to pay, not only to achieve such level but also to maintain it.

The notorious aspect is that although being the less conscious intelligence, its evolution empowers the possibilities of the functional intelligences of individuals.

Business Functionality of Ethical Intelligence

The discovery of ethical intelligence opened new possibilities to influence individuals’ evolution. Ethical intelligence in business defines the value adding possibilities, the influence on the environment, time management, strategic planning and focusing.

The apparent paradox is that it is the deepest intelligence of the human mind, but at the same time it is the intelligence that evolves with the maturity of individuals and can be influenced.

It has to be considered that in the business world different activities require different ethical approaches in order to be successful. For example:

Pyramid of Ethical IntelligencesA business is consistent when the individuals dealing with it have the ethics required by the activity.

When the ethics is inferior to what is needed, it necessarily inhibits growth installing a “business growth virus” in the organization.

If the ethics used by individuals is superior to what is needed, they install a “business profit virus” in the organization that increases costs and affects profitability.

Ethics is implicit in everyday actions, including language. Therefore, it can be defined, measured and fostered.

The rational knowledge of ethical intelligence has an enormous benefit for individuals in organizations in order to ensure consistency for growth and profitability.

Unicist Press Committee

NOTE: The Unicist Research Institute was the pioneer in using the unicist logical approach in complexity science research and became a private global decentralized leading research organization in the field of human adaptive systems. It has an academic arm and a business arm.
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The Unicist Theory solved the approach to complexity

Unicist Theory, its Applications and Scientific EvidencesThe Unicist Theory made adaptive systems manageable and gave an epistemological structure to complexity sciences. As it is known, the management of complexity has been an unsolved challenge for sciences. This challenge has been faced in 1976 by Peter Belohlavek at The Unicist Research Institute, which became a pioneering organization in the development of concrete solutions to manage the complex adaptive systems by developing a logical approach that uses the Unicist Theory.

A double dialectical logical approach to manage complex problems has been discovered. This approach is based on the discovery that complex systems have a triadic structure that emulates the ontogenetic intelligence of nature, represented by a purpose, an active principle and an energy conservation principle and their integration. The Unicist Theory that solved the approach to complexity includes the Ontogenetic Intelligence of Nature, the Unicist Ontology, the Unicist Logic, the Unicist Conceptualization, the Unicist Ontology of Evolution, the Ontogenetic Maps and the Unicist Objects.

There are fields that are generally accepted as being complex such as: life sciences, social sciences, anthropology, political sciences, economic sciences, behavioral sciences, medicine, psychology, education, businesses, ecology and meteorology.

The complexity of a system is intrinsic, which means that it does not depend on the perception of an individual. But in order to apprehend a complex system it is necessary that the person emulates the system in mind, which fully depends on the individual. This required defining what a complex system is.

Science dealt with complexity using multiple palliatives but without achieving consensus of what complex systems are. The main problem to manage complexity is that all the elements of the complex system are integrated by bi-univocal conjunctions without the possibility of the existence of disjunctions, that the boundaries of the objects that integrate the complex system are open and that the system is open in itself. The only measurable facts are the results that such system produces.

The most difficult task was the completion of the scientific evidences to confirm the functionality of the solutions, which demanded thousands of applications until they could be synthesized. The scientific evidences of the Unicist Theory were: the functionality of amino acids, the structure of atoms, the structure of biological entities, the nervous system, the similarity between natural and social objects, the fact that unicist concepts behave as stem cells and that thinking processes are homologous to the functionality of electricity.

The Unicist Theory was used to develop applications in Life Sciences, Future Research, Business, Education, Healthcare and Social and Human behavior. Now complex adaptive systems became manageable and complexity science received its epistemological structure. Palliatives to deal with complexity will continue to be used until people accept that complexity needs to be approached in its nature.

Learn more: http://www.unicist.org/repo/#Basics

Executive Committee

NOTE: The Unicist Research Institute was the pioneer in using the unicist logical approach in complexity science research and became a private global decentralized leading research organization in the field of human adaptive systems. It has an academic arm and a business arm.
https://www.unicist-school.org/theoryofevolution/wp-content/uploads/2014/11/turi.pdf

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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

Aspect

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
Variables
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
Systems

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).

Synthesis

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.
https://www.unicist-school.org/theoryofevolution/wp-content/uploads/2013/11/turi.pdf

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