Introduction to Artificial Intelligence:
Search and Reasoning

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Email sushanthmukkamalla@gmail.com for code

  • Probabilistic Reasoning

    Using logic and probability from background information to handle uncertain situations.

  • Hangman

    Used the Naive Bayes model and probabilistic reasoning to accurately pick the next best guess in a game of Hangman.

  • Variable Elimination Algorithm

    A simple and general exact inference algorithm in probabilistic graphical models.

  • Using probabilistic models to predict the next word in the sequence given the words that precede it.

    Description.

  • Expectation-Maximization

    An iterative method to find maximum likelihood estimates of parameters in statistical models, where the model depends on unobserved latent variables.

  • Viterbi Algorithm

    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.

  • Pacman: Reinforcement Learning

    Implement value iteration and Q-learning, then apply them to a simulated robot controller (Crawler) and Pacman.

  • Value Iteration

    Computing an optimal Markov Decision Process policy and its value.