A software tool designed to model and analyze systems that transition between different states according to probabilistic rules. For example, such a tool could predict weather patterns based on historical transition probabilities between sunny, cloudy, and rainy states. The underlying mathematical framework employs a matrix representing transition probabilities between each state.
These tools provide a powerful method for predicting future behavior in complex systems characterized by randomness. This predictive capability has numerous applications in fields like finance, weather forecasting, and computer science, facilitating risk assessment, resource allocation, and system optimization. Pioneering work by Andrey Markov in the early 20th century laid the foundation for this analytical approach.
