Artificially intelligent agents perceive the world, solve problems by combining data, knowledge, and judgement, and act in the world. Examples of AI agents range from web search engines to scheduling agents to humanoid robots. This course will cover representations and algorithms in several core subareas of artificial intelligence, beginning with advanced search and planning. We will then tackle more advanced topics selected in response to student interests. Candidate topics include (but are not limited to): evolutionary computation and particle filters, ensemble learning, Bayesian networks, Markov and other time-series models, data mining, information retrieval, and natural language interpretation/generation.