Introduction to Artificial Intelligence by Thomas P Trappenberg
This note covers introduction and history, Search, Robotics
and motion planning, Constraint satisfaction problem, Machine learning, Learning
machines and the perceptron, Regression, classification and maximum likelihood,
Support vector machines, Learning Theory, Generative models and Naïve Bayes,
Unsupervised learning, Reinforcement learning, Probabilistic Reasoning, Bayesian
networks and Markov models.
Author(s): Thomas P Trappenberg,
Dalhousie University
208 Pages