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Using logic and probability from background information to handle uncertain situations.
Used the Naive Bayes model and probabilistic reasoning to accurately pick the next best guess in a game of Hangman.
A simple and general exact inference algorithm in probabilistic graphical models.
Description.
An iterative method to find maximum likelihood estimates of parameters in statistical models, where the model depends on unobserved latent variables.
A dynamic programming algorithm for finding the most likely sequence of hidden states, called the Viterbi path, that results in a sequence of observed events.
Implement value iteration and Q-learning, then apply them to a simulated robot controller (Crawler) and Pacman.
Computing an optimal Markov Decision Process policy and its value.