algorithmic information theory
Algorithmic information theory, also known as Kolmogorov complexity, is a branch of information theory that quantifies the amount of information or complexity in a string of data by measuring the size of the shortest possible algorithm or program that can produce it. It focuses on the inherent complexity of information rather than the specific representation or format used.
Requires login.
Related Concepts (1)
Similar Concepts
- algorithmic bias
- algorithmic complexity
- algorithmic complexity attacks
- algorithmic decision making
- algorithmic decision-making
- cellular automata and information theory
- cellular automata in information theory
- computability theory
- entropy in information theory
- information theory
- information theory and statistical mechanics
- information theory in complex systems
- quantum entanglement and information theory
- quantum information theory
- theory of computation