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KI-Glossar

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Complex Adaptive System

Set of interconnected entities capable of modifying its structure and behavior in response to environmental changes through autonomous learning mechanisms.

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Chaos Theory

Study of non-linear dynamical systems exhibiting extreme sensitivity to initial conditions, making their long-term behavior unpredictable despite local determinisms.

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Adaptive Feedback

Mechanism by which a system adjusts its internal parameters in response to the results of its previous actions, enabling continuous optimization of its behavior.

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Non-linear Dynamical System

System whose temporal evolution is governed by non-linear differential equations, capable of complex behaviors like bifurcations, limit cycles, and chaos.

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Hopfield Network

Fully connected recurrent neural network functioning as an associative memory, converging to stable states corresponding to memorized patterns.

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Ant Colony Algorithm

Metaheuristic inspired by the behavior of ants finding optimal paths through pheromone deposition and tracking, applied to complex combinatorial optimization.

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Evolutionary Algorithms

Family of metaheuristics inspired by biological evolution using variation, selection, and inheritance to solve complex optimization problems.

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Hybrid Adaptive System

Architecture combining multiple learning and adaptation paradigms to exploit their complementary strengths in complex dynamic environments.

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Adaptive Metaheuristic

High-level optimization strategy that dynamically adjusts its parameters and operators based on problem characteristics and observed performance.

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Self-Organized Criticality

Critical state spontaneously reached by certain complex systems where events of all sizes follow power laws without external control parameters.

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Echelon Network

Hierarchical neural architecture where each level processes increasing abstractions, enabling progressive adaptation to environments of variable complexity.

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Meta-Adaptive Learning

Ability of a system to modify not only its performance but also its learning strategies themselves based on evolving environmental conditions.

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