Artificial Intelligence

[revised 10/21/2009]

For this concentration, students must take CS 221 to satisfy the core AI requirement. In addition, they must complete a total of six courses from the following list, including at least three of the courses marked in *boldface with surrounding asterisks* (drawn from at least two areas):

1. Knowledge representation and reasoning: Logic and Automated Reasoning (CS 157); *Rational Agency and Intelligent Interaction (CS 222/Phil 358)*; *Reasoning Methods in AI (CS 227)*; *Structured Probabilistic Models: Principles and Techniques (CS 228)*; Formal Methods for Reactive Systems (CS 256); Modal Logic (Phil 154).
2. Natural language processing: *Natural-Language Processing (CS 224N/Linguist 280)* or From Languages to Information (CS 124/Linguist 180) (but not both); *Speech Recognition and Synthesis (CS 224S/Linguist 285)*; *Natural Language Understanding (CS 224U/Linguist 188/288)*.
3. Learning: *Machine Learning (CS 229)*; Approximate Dynamic Programming (MS&E 339); Modern Applied Statistics: Learning (Stat 315A); Modern Applied Statistics: Data Mining (Stat 315B).
4. Robotics and vision: *Introduction to Robotics (CS 223A)*; *Introduction to Computer Vision (CS 223B)*; Experimental Robotics (CS 225A); Robot Programming Laboratory (CS 225B); *Statistical Techniques in Robotics (CS 226)*, *Motion Planning (CS 326A)*.
5. Additional topics: *Multi-agent Systems (CS 224M)*; General Game Playing (CS 227B); Topics in Artificial Intelligence (CS 329) [with approval of advisor]; Introduction to Biomedical Informatics: Fundamental Methods (CS 270/Biomedin 210); Introduction to Biomedical Informatics: Biomedical Systems Engineering (CS 271/Biomedin 211); Representations and Algorithms for Computational Molecular Biology (CS 274/BioE 214/Biomedin 214/Gene 214); Phenomenological Foundations of Cognition, Language, and Computation (CS 378).
6. Mathematical foundations: Game Theory and Economic Applications (Econ 160); Introduction to Linear Dynamic Systems (EE 263); Convex Optimization (EE 364A/B); Information Theory (EE 376A/B); Computability and Logic (Phil 152) [if not taken for the core]; Stochastic Decision Models (MS&E 251); Introduction to Control Design Techniques (Engr 205); Analysis and Control of Nonlinear Systems (Engr 209A); Linear Algebra and Matrix Theory (Math 113); Mathematical Methods for Robotics, Vision, and Graphics (CS205A); Introduction to Automata and Complexity Theory (CS154) [if not taken for the core].