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Definitions by Abzugal

Paraconsistent Logic

Logic that allows the existence of contradictions (A and not-A) without every proposition becoming derivable (the principle of explosion). It rejects the law of non-contradiction in certain contexts. Useful in legal systems (conflicting norms), inconsistent databases, and scientific theories in transition. It is not "anything goes": it restricts the effects of contradiction.
Paraconsistent Logic Example: "In paraconsistent logic, if a database says 'John is an adult' and 'John is not an adult', that does not mean 'the moon is made of cheese.' The inconsistency remains localized, not exploding the system."

Fuzzy Logic

A multi-valued logic where truth values vary continuously between 0 (false) and 1 (true), allowing handling of imprecision and vagueness. It contradicts the principle of the excluded middle (something is either true or false). Used in control systems (air conditioning, ABS brakes), artificial intelligence, and decision theory. It is not "logical relativism" – it has well-defined rules.
Fuzzy Logic Example: "In fuzzy logic, the statement 'today is hot' can have a truth degree of 0.7 if the temperature is 28°C – neither completely true nor false, and an air conditioner uses that to adjust ventilation."
Fuzzy Logic by Abzugal May 26, 2026

Complex Dynamical Science Theory

A view of science as a complex dynamical system (nonlinear, emergent, historical). Scientific theories evolve through interactions among communities, data, instruments, economic interests, and feedbacks. There is no fixed "scientific method" – it emerges as an attractor in a space of possibilities. It rejects both linear positivism and anarchic relativism.
Complex Dynamical Science Theory Example: "Complex Dynamical Science Theory explains scientific revolutions (Kuhn) as bifurcations in theory space: small anomalies accumulate until an 'inflection point' shifts the paradigm, unpredictably."

Fuzzy Science Theory

Application of fuzzy logic (truth degrees between 0 and 1) to the philosophy and practice of science. It proposes that scientific statements are not true or false in a binary way, but belong to blurred categories. Hypotheses have degrees of confirmation, theories have degrees of acceptance, and demarcation itself is fuzzy. It offers an alternative to the excessive rigor of neopositivism and the rigidity of Popper's criterion.
Fuzzy Science Theory Example: "In Fuzzy Science Theory, saying 'general relativity is true' means a truth degree close to 0.99 – yet there are small observational anomalies preventing absolute 1."

Paraconsistent Science Theory

feminine noun An approach that allows dealing with contradictions in science without logical collapse (the principle of explosion). In scientific practice, contradictory theories often coexist for long periods (e.g., relativity and quantum mechanics). Paraconsistent logic formalizes this tolerance. Paraconsistent Science Theory holds that contradictions can be productive and do not necessarily mean falsehood.

Example: "In Paraconsistent Science Theory, wave-particle duality is not a logical error – it is a well-behaved contradiction that lives within quantum mechanics without exploding the theoretical edifice."

Spectrum of Science Theory

feminine noun An epistemological proposal that replaces the rigid dichotomy of science vs. pseudoscience with a continuous spectrum. On this spectrum, knowledge practices vary in degrees of methodological rigor, falsifiability, consensus, utility, and empirical basis. At the strong pole: physics, chemistry. In the middle: psychology, economics, historical sciences. At the weak pole: some hermeneutic or speculative traditions. It avoids absolute demarcations.
Spectrum of Science Theory Example: "In the Spectrum of Science Theory, homeopathy is not simply 'pseudoscience' – it lies at a weak extreme due to lack of biological plausibility and evidence, while psychoanalysis lies in the middle, with method but low falsifiability."

Complex Dynamical Computing

feminine noun A computing paradigm inspired by complex dynamical systems. Instead of sequential deterministic algorithms, it uses networks of nonlinear elements, feedback, emergence, and analog computing. It includes recurrent neural networks, reservoir computing, chaotic systems for pattern generation, and morphological computing (using the system's physics to compute). Promising for adaptive robotics and brain simulation.
Complex Dynamical Computing Example: "A robot with complex dynamical computing does not program steps; it has a chaotic network that evolves – the leg adjusts to the terrain not because it was instructed, but because the system as a whole 'finds' the stable trajectory."

Complex Dynamical Systems

Systems composed of many interacting agents whose collective behavior is not linearly deducible from the parts. They exhibit sensitivity to initial conditions (butterfly effect), emergence, feedback loops, self-organization, and criticality. Examples: climate, brain, economy, ecosystems. They differ from merely complicated systems (a clock) because they are unpredictable in the long term.
Complex Dynamical Systems Example: "A flock of birds is a complex dynamical system: each bird follows simple local rules, but the global movement of the flock emerges without a central leader – and no one can precisely predict its trajectory."

Complex Dynamical Systems Theory

feminine noun Interdisciplinary field that formally studies nonlinear, chaotic, adaptive, and emergent systems. It integrates mathematics (differential equations, chaos theory), physics, biology, economics, and social sciences. It seeks to identify universal patterns (attractors, fractals, power laws) regardless of domain. It challenged the classical reductionist paradigm by showing that the whole is more than the sum of its parts.

Example: "Complex Dynamical Systems Theory explains why small changes in traffic (one car braking) can create massive jams – and why predicting weather beyond 10 days is mathematically impossible."