Laplace's demon is a supreme intelligence who could completely predict the one possible future given the Newtonian dynamical laws of classical physics and perfect knowledge of the positions and velocities of all the particles in the world.
The branch of mathematics known as Chaos Theory focuses on the behavior of systems that are highly sensitive to initial conditions.
In principle, the deterministic systems that chaos theory attempts to analyze can be predicted, but uncertainty in a forecast increases exponentially with elapsed time.
[2] As documented in,[3] three major kinds of butterfly effects within Lorenz studies include: the sensitive dependence on initial conditions,[4][5] the ability of a tiny perturbation to create an organized circulation at large distances,[6] and the hypothetical role of small-scale processes in contributing to finite predictability.
In the study of human–computer interaction, predictability is the property to forecast the consequences of a user action given the current state of the system.
A contemporary example of human-computer interaction manifests in the development of computer vision algorithms for collision-avoidance software in self-driving cars.
Researchers at NVIDIA Corporation,[10] Princeton University,[11] and other institutions are leveraging deep learning to teach computers to anticipate subsequent road scenarios based on visual information about current and previous states.
Significant debate exists in the scientific community over whether or not a person's behavior is completely predictable based on their genetics.
[15] The study of predictability often sparks debate between those who believe humans maintain complete control over their free-will and those who believe our actions are predetermined.
[20][21] The results, with attractor coexistence, suggest that the entirety of weather possesses a dual nature of chaos and order with distinct predictability.
[22] Using a slowly varying, periodic heating parameter within a generalized Lorenz model, Shen and his co-authors suggested a revised view: “The atmosphere possesses chaos and order; it includes, as examples, emerging organized systems (such as tornadoes) and time varying forcing from recurrent seasons”.
Examples of US macroeconomic series of interest include but are not limited to Consumption, Investment, Real GNP, and Capital Stock.