Closed Loop Interval Ontology
       The Digital Integration of Conceptual Form


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Project under development
Evolving and coalescing

Guiding motivation
Why we do this

Objectives and strategy
Reconciliation and integration

Reconciliation of perspectives
Holistic view on alternatives

What is truth?
How do we know?

What is a concept?
Definitions and alternatives

How meaning is created

Universal Hierarchy
Spectrum of levels

A Universal Foundation
The closed loop ensemble contains
all primary definitions

Dimensions of set theory

Venn diagrams
Topology of sets

Objects in Boolean Algebra
How are they constructed?

Core vocabulary
Primary terms

Core terms on the strip
Closed Loop framework

Hierarchical models

Digital geometry
Euclid in digital space

The digital integration
of conceptual form

Compositional semantics

Closed loop interval ontology
How it works

Cognitive science
The integrated science of mind

What does it mean?

Formal systematic definitions
Core terms

Data structures
Constructive elements
and building blocks

Preserving data under transformation

Steady-state cosmology
In the beginning

Semantic ontology
Domain and universal

From other sources

Cognitive science
The integrated science of mind

Cognitive science is the interdisciplinary study of the mind

It is broadly inclusive, and considers

  • Psychology
  • Computer science
  • Mathematics and logic
  • Semantics

This project has deep roots in cognitive science and epistemology. We draw on these topics and we explore and develop new solutions for global problems.

Cognitive science at Berkeley
Computer science

Cognitive science at Berkeley

Welcome to UC Berkeley Cognitive Science

The main objective of the discipline of Cognitive Science is to provide a framework for bringing all the many disciplines that study the mind together into a cohesive whole. Students in our program draw on psychology, linguistics, computer science, philosophy, neuroscience, and anthropology, among other fields, to illuminate how the human mind works, and why it works the way it does. Many influential ideas within cognitive science originated at Berkeley. The program draws on over forty affiliated faculty from a variety of departments, and is closely integrated with cognitive science research efforts across the campus.


Computer science

Computer science is the study of algorithmic processes, computational machines and computation itself.

Computer science is the study of algorithmic processes, computational machines and computation itself.[1] As a discipline, computer science spans a range of topics from theoretical studies of algorithms, computation and information to the practical issues of implementing computational systems in hardware and software.[2][3]

Its fields can be divided into theoretical and practical disciplines. For example, the theory of computation concerns abstract models of computation and general classes of problems that can be solved using them, while computer graphics or computational geometry emphasize more specific applications. Algorithms and data structures have been called the heart of computer science.[4] Programming language theory considers approaches to the description of computational processes, while computer programming involves the use of them to create complex systems. Computer architecture describes construction of computer components and computer-operated equipment. Artificial intelligence aims to synthesize goal-orientated processes such as problem-solving, decision-making, environmental adaptation, planning and learning found in humans and animals. A digital computer is capable of simulating various information processes.[5] The fundamental concern of computer science is determining what can and cannot be automated.[6] Computer scientists usually focus on academic research. The Turing Award is generally recognized as the highest distinction in computer sciences.



The philosopher of computing Bill Rapaport noted three Great Insights of Computer Science:[52]

Gottfried Wilhelm Leibniz's, George Boole's, Alan Turing's, Claude Shannon's, and Samuel Morse's insight: there are only two objects that a computer has to deal with in order to represent "anything".[note 4] All the information about any computable problem can be represented using only 0 and 1 (or any other bistable pair that can flip-flop between two easily distinguishable states, such as "on/off", "magnetized/de-magnetized", "high-voltage/low-voltage", etc.). See also: Digital physics

Alan Turing's insight: there are only five actions that a computer has to perform in order to do "anything". Every algorithm can be expressed in a language for a computer consisting of only five basic instructions:[53] move left one location; move right one location; read symbol at current location; print 0 at current location; print 1 at current location. See also: Turing machine

Corrado Böhm and Giuseppe Jacopini's insight: there are only three ways of combining these actions (into more complex ones) that are needed in order for a computer to do "anything".[54] Only three rules are needed to combine any set of basic instructions into more complex ones: sequence: first do this, then do that; selection: IF such-and-such is the case, THEN do this, ELSE do that; repetition: WHILE such-and-such is the case, DO this. Note that the three rules of Boehm's and Jacopini's insight can be further simplified with the use of goto (which means it is more elementary than structured programming).


Collaborative ontology
Everything derived from the continuum
Cognitive science
Axiomatic systems
Taxonomy and dimensionality