AI-ordlista
Den kompletta ordlistan över AI
Complex Adaptive System
Set of interconnected entities capable of modifying its structure and behavior in response to environmental changes through autonomous learning mechanisms.
Chaos Theory
Study of non-linear dynamical systems exhibiting extreme sensitivity to initial conditions, making their long-term behavior unpredictable despite local determinisms.
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.
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.
Hopfield Network
Fully connected recurrent neural network functioning as an associative memory, converging to stable states corresponding to memorized patterns.
Ant Colony Algorithm
Metaheuristic inspired by the behavior of ants finding optimal paths through pheromone deposition and tracking, applied to complex combinatorial optimization.
Evolutionary Algorithms
Family of metaheuristics inspired by biological evolution using variation, selection, and inheritance to solve complex optimization problems.
Hybrid Adaptive System
Architecture combining multiple learning and adaptation paradigms to exploit their complementary strengths in complex dynamic environments.
Adaptive Metaheuristic
High-level optimization strategy that dynamically adjusts its parameters and operators based on problem characteristics and observed performance.
Self-Organized Criticality
Critical state spontaneously reached by certain complex systems where events of all sizes follow power laws without external control parameters.
Echelon Network
Hierarchical neural architecture where each level processes increasing abstractions, enabling progressive adaptation to environments of variable complexity.
Meta-Adaptive Learning
Ability of a system to modify not only its performance but also its learning strategies themselves based on evolving environmental conditions.