8 min read. Monte Carlo simulations are used to model the probability of different outcomes in a process that cannot easily be predicted due to the intervention of random variables. Students will spend a considerable amount of time writing programs to implement the concepts covered in the course. 7 min read.
The method of Design of Experiments make use of social graphs that enables simulation of data in a standardized approach. This text is a very simple, didactic introduction to this subject, a mixture of history, mathematics and mythology.
Monte Carlo (MC) methods are a subset of computational algorithms that use the process of repeated random sampling to make numerical estimations of unknown parameters. Topics covered include plotting, stochastic programs, probability and statistics, random walks, Monte Carlo simulations, modeling data, optimization problems, and clustering. They allow for the modeling of complex situations where many random variables are involved, and assessing the impact of risk. So you want to use Monte Carlo Tree Search (MCTS), but your game has imperfect information, and an element of chance.That’s difficult! The Monte Carlo method is an simple way to solve very difficult probabilistic problems. In this blog we’ll apply MCTS to such a game; Kariba.

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