The Epistemology to deal with Complex Adaptive Environments
The Unicist Epistemology is based on the development of logical foundations and empirical justifications to sustain human knowledge. This epistemology is a pragmatic, structural and functionalist approach to knowledge.
The pragmatism deals with the goal of this epistemology, which is to provide reliable knowledge in order to generate added value. At the same time, structuralism is required to integrate the knowledge of an entity and its restricted and wide contexts. Finally, functionalism makes results be a core aspect of the validity of knowledge.
Knowledge is such when its use allows individuals to better adapt to an environment. But to be used, such knowledge needs to be stored in the individual’s long-term memory.
The credibility of knowledge depends on having found the fundamentals that integrate the concept that defines the nature of an entity and having the necessary empirical justifications that make the acceptance of knowledge tangible.
The Unicist Epistemology was developed to build reliable knowledge to deal with complex adaptive environments.
This is a synthesis of the Unicist Epistemology that has been used for more than 15 years, since the ontology of destructive and non-destructive tests was developed, to build the knowledge objects of the applications of the Unicist Theory.
This synthesis begins with the presentation of a major discovery, which is the fact that the concepts that individuals have stored in their long-term memory drive their actions. That is why the fundamentals that integrate these concepts are the drivers of human actions.
The validation of concepts and fundamentals requires that individuals develop destructive and non-destructive tests, while the confirmation of operational knowledge only requires using non-destructive tests.
The Unicist Epistemology provides, on the one hand, the basics of foundations, which deal with fundamental analysis, and on the other hand, the basics of cause-effect knowledge, which sustain the empirical justifications of knowledge.
Language, as a tool of the conscious reasoning structure of humans, is a necessary condition to build conscious knowledge. Different types of languages allow building different types of knowledge.
The unicist epistemology includes the structure of the destructive and non-destructive tests that are used to confirm the validity of knowledge. It includes the description of how the knowledge building is driven by perception and credibility and how the ontology of signs sustains the building of reliable knowledge.
Unicist Epistemology: What for?
The Unicist Ontology of Research
Innovation is the essential purpose of research. Research is developed to be able to innovate within a given reality. This influence may consist in building, curing, developing, repairing, or whatever human needs require.
The essential concept of research is to find innovations to improve the value added. In order to do so, research builds foundations and explains the facts of that reality.
When researching truth, in a non-religious sense, there is a great difficulty to develop “real” research, being limited by the capability to understand facts.
That means there is no possibility for a person who has the talent of researching beyond the accepted limits of knowledge to develop researches based on non-accepted knowledge.
The personal histories of Galileo, Newton, and Tesla are examples of this assertion.
To understand the process of research one has to know the limits of one’s knowledge to be able to accept evidences without being able to comprehend their groundings.
Description of the Functional Concept of Research
To do so the drivers are functional experiments based on universal secure knowledge.
The limits of acceptance of research are given by the capacity to explain facts based on artificial experiments that are sustained by specific secure knowledge.
But if the limits of acceptance prevail research becomes fallacious.
There are four basic segments of research and a pseudo-research approach.
Analogical Research – Pseudo research approach
This research is based on the comparison of a fact with analogical examples, opinions, or components. Its basic research tool is statistics, and its validation is given by the consistency between the analogy and the homology of the data being considered as valid in the research.
This research is based on finding the cause-effect relationship between the facts being researched and their immediate causes. Descriptions, statistics, mathematical inferences, and syncretic language are the tools of this research.
This research is functional in fields where corrective actions are functional and possible to achieve goals. When corrective actions are not possible or dysfunctional this research approach is valueless.
This research is based on the logical and mathematical relations between the facts researched and their causes in a restricted field. Analysis is based on dividing a reality into its components until finding a secure knowledge.
After secure knowledge is found, the reconstruction of the wholeness of facts enters the world of probabilities. Logic, mathematics, and analytic language are the tools of this research.
This research is based on finding the variables of a given reality and making all the functional experiences to secure the knowledge of facts. Descriptions, analysis, cause-effect relations, mathematics, and factual language are the research tools of this approach.
This research is functional in the field of materialistic researches where probabilities are functional to approach reality. Where probabilities are not good enough, this approach is dysfunctional.
This research is based on finding the ontological structure of a given reality to access its “know why.” Descriptions, analysis, cause-effect relations, reflections, mathematics, and synthetic language are the inputs to find the ontological structure of a given reality.
This research is functional in the field of knowledge where the comprehension of its wholeness is necessary. This research is functional to integrate the preceding research approaches to secure conclusions on complex realities.
All these approaches must be used to build secure knowledge about unknown facts. That is the meaning of the unicist secure knowledge acquisition.
Functional conceptual structure of the complex systems research
Complex systems are studied seeking the foundation through experimentation based on preexisting secure knowledge.
Research necessarily implies experimentation, which must allow repetition. That is to say, regardless of the number of times that the experience is carried out the result should always be the same.
Results from experimentation must be verifiable, that is, they have to able to be measured objectively, subjectively or through forecast.
In addition, the experimentation of the complex system under study must “work”, that is, this should be a real activity that produces a result for which such system has been designed. To work means an actual activity that cannot be simulated.
Research is based on preexisting secure knowledge. This knowledge must have quality assurance, be operable and verified.
Research on complex systems cannot be built on the basis of hypothetic knowledge. When there are only hypothesis then real foundations cannot be reached, instead, hypothetical foundations are built.
Complexity Research of Complex Adaptive Systems
Complexity Sciences are defined as the scientific approach to deal with complex adaptive systems.
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.
The Unicist Standard for Complexity Research was developed based on the characteristics of adaptive systems considered in their complexity.
Some of the characteristics of such systems are:
- Open boundaries
- Bi-univocity of its components
- The existence of conjunctions without disjunctions
- The inexistence of observers
The consequence was the substitution of an epistemologically invalid approach to complex problems, dividing them into variables, which are inexistent, by a unicist ontological approach driven by objects, in which objects are integrated as subsystems in adaptive systems, following the rules of the ontogenetic intelligence of nature.
The development of the unicist ontological research methodology allowed discovering the unicist ontogenetic maps and ontogenetic algorithms of human adaptive systems making them reasonable, understandable and predictable.
The unicist approach to complexity sciences integrates ontology, science and actions in a unified field.
Therefore the research on human complex adaptive systems cannot be done through artificial experiments or simulations. It has to be done in an environment of real action. In the unicist approach doing and researching are integrated in a unified field.
The unicist ontological research model enabled the definition of the field of possibilities of an adaptive system and to enter then in the field of probabilities of the occurrence of events.
The concepts of falsification and validation, applicable to systemic sciences, were replaced by the use of destructive and non destructive pilot tests.
The presentation of the knowledge of complex adaptive systems includes two different levels of information:
- The synthesis: that includes the discoveries of the unicist ontological structures and the ontogenetic maps written in unicist standard language.
- The research process: that describes the steps of the research process.
Understanding Complex Adaptive Systems
A paradigm shift in sciences was necessary in order to understand and influence complex adaptive systems. This was needed because such systems have open boundaries and have no univocal cause-effect relationships. Therefore they cannot be approached by systemic sciences.
This approach integrates, in a unified field, the “KNOW WHY” required to apprehend complexity with the “KNOW HOW” provided by empiricism. It simplified complex adaptive systems making them reasonable, understandable and predictable. This approach has integrated systemic sciences with complexity sciences
The unicist approach has introduced a paradigm shift in sciences applied to complex adaptive systems that drove from an empirical approach to a pragmatic, structuralist and functionalist approach to deal with complex environments integrating the preexisting empiricism.
This is an upgrade in sciences that integrated complexity sciences with systemic sciences that allowed emulating the organization of nature by developing a logic based and object driven approach to manage the adaptive aspects of reality.