Self-organizing in the context of Operator grammar

Self-organizing in the context of Operator grammar

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⭐ Core Definition: Self-organizing

Self-organization, also called spontaneous order in the social sciences, is a process where some form of overall order arises from local interactions between parts of an initially disordered system. The process can be spontaneous when sufficient energy is available, not needing control by any external agent. It is often triggered by seemingly random fluctuations, amplified by positive feedback. The resulting organization is wholly decentralized, distributed over all the components of the system. As such, the organization is typically robust and able to survive or self-repair substantial perturbation. Chaos theory discusses self-organization in terms of islands of predictability in a sea of chaotic unpredictability.

Self-organization occurs in many physical, chemical, biological, robotic, and cognitive systems. Examples of self-organization include crystallization, thermal convection of fluids, chemical oscillation, animal swarming, neural circuits, and black markets.

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👉 Self-organizing in the context of Operator grammar

Operator grammar is a mathematical theory of human language that explains how language carries information. This theory is the culmination of the life work of Zellig Harris, with major publications toward the end of the last century. Operator grammar proposes that each human language is a self-organizing system in which both the syntactic and semantic properties of a word are established purely in relation to other words. Thus, no external system (metalanguage) is required to define the rules of a language. Instead, these rules are learned through exposure to usage and through participation, as is the case with most social behavior. The theory is consistent with the idea that language evolved gradually, with each successive generation introducing new complexity and variation.

Operator grammar posits three universal constraints: dependency (certain words depend on the presence of other words to form an utterance), likelihood (some combinations of words and their dependents are more likely than others) and reduction (words in high likelihood combinations can be reduced to shorter forms, and sometimes omitted completely). Together these provide a theory of language information: dependency builds a predicate–argument structure; likelihood creates distinct meanings; reduction allows compact forms for communication.

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Self-organizing in the context of Life

Life is matter that has biological processes, such as signaling and the ability to sustain itself. It is defined descriptively by the capacity for homeostasis, organisation, metabolism, growth, adaptation, response to stimuli, and reproduction. All life over time eventually reaches a state of death, and none is immortal. Many philosophical definitions of living systems have been proposed, such as self-organizing systems. Defining life is further complicated by viruses, which replicate only in host cells, and the possibility of extraterrestrial life, which is likely to be very different from terrestrial life. Life exists all over the Earth in air, water, and soil, with many ecosystems forming the biosphere. Some of these are harsh environments occupied only by extremophiles. The life in a particular ecosystem is called its biota.

Life has been studied since ancient times, with theories such as Empedocles's materialism asserting that it was composed of four eternal elements, and Aristotle's hylomorphism asserting that living things have souls and embody both form and matter. Life originated at least 3.5 billion years ago, resulting in a universal common ancestor. This evolved into all the species that exist now, by way of many extinct species, some of which have left traces as fossils. Attempts to classify living things, too, began with Aristotle. Modern classification began with Carl Linnaeus's system of binomial nomenclature in the 1740s.

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Self-organizing in the context of Complex adaptive system

A complex adaptive system (CAS) is a system that is complex in that it is a dynamic network of interactions, but the behavior of the ensemble may not be predictable according to the behavior of the components. It is adaptive in that the individual and collective behavior mutate and self-organize corresponding to the change-initiating micro-event or collection of events. It is a "complex macroscopic collection" of relatively "similar and partially connected micro-structures" formed in order to adapt to the changing environment and increase their survivability as a macro-structure. The Complex Adaptive Systems approach builds on replicator dynamics.

The study of complex adaptive systems, a subset of nonlinear dynamical systems, is an interdisciplinary matter that attempts to blend insights from the natural and social sciences to develop system-level models and insights that allow for heterogeneous agents, phase transition, and emergent behavior.

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LINKED FROM (PARENTS)
← Life ← Complex adaptive system ← Complex adaptive systems ← Operator grammar
LINKS TO (CHILDREN)
Hydrothermal synthesis → Amorphous → Nanowire → Spontaneous order → Social science → Order and disorder → System → Statistical fluctuations → Positive feedback → Robustness → Self-healing material → Perturbation theory → Chaos theory → Predictability → Physics → Chemistry → Biology → Robotics → Cognitive → Crystallization → Convection → Chemical oscillator → Swarming → Neural circuit → Black market →