Non-Deterministic Process
A non-deterministic process is a computational or system behavior where the outcome is not uniquely determined by the initial state and inputs, often involving randomness, concurrency, or external factors. It contrasts with deterministic processes, which always produce the same result given identical conditions. This concept is fundamental in fields like distributed systems, probabilistic algorithms, and quantum computing.
Developers should understand non-deterministic processes when working with systems where outcomes vary, such as in concurrent programming (e.g., race conditions), machine learning (e.g., stochastic gradient descent), or simulations (e.g., Monte Carlo methods). It helps in debugging, designing robust systems, and leveraging randomness for optimization or modeling uncertainty in applications like cryptography or game AI.