printer friendly pageCS 221: Artificial Intelligence: Principles and Techniques
Artificial intelligence (AI) has had a huge impact in many areas, including medical diagnosis, speech recognition, robotics, web search, advertising, and scheduling. This course focuses on the foundational concepts that drive these applications. In short, AI is the mathematics of making good decisions given incomplete information (hence the need for probability) and limited computation (hence the need for algorithms). Specific topics include search, constraint satisfaction, game playing,n Markov decision processes, graphical models, machine learning, and logic. Prerequisites:
CS 103 or
CS 103B/X,
CS 106B or
CS 106X,
CS 109, and
CS 161 (algorithms, probability, and object-oriented programming in Python). We highly recommend comfort with these concepts before taking the course, as we will be building on them with little review.
Terms: Aut, Spr
| Units: 3-4
Instructors:
Anari, N. (PI)
;
Charikar, M. (PI)
;
Koyejo, S. (PI)
;
Liang, P. (PI)
;
Phatak, U. (PI)
;
Sadigh, D. (PI)
;
Agarwal, R. (TA)
;
Bruzzese, T. (TA)
;
Camacho, S. (TA)
;
Dixit, A. (TA)
;
Frausto, J. (TA)
;
Hejna, J. (TA)
;
Hu, G. (TA)
;
Jeon, H. (TA)
;
Kansal, A. (TA)
;
Khurana, A. (TA)
;
Ko, J. (TA)
;
Lee, A. (TA)
;
Li, C. (TA)
;
Li, K. (TA)
;
Lin, K. (TA)
;
Liu, S. (TA)
;
Melo, L. (TA)
;
Michaels, J. (TA)
;
Nie, N. (TA)
;
Pampari, A. (TA)
;
Pandya, D. (TA)
;
Prakash, E. (TA)
;
Roman, E. (TA)
;
Ryan, M. (TA)
;
Taori, R. (TA)
;
Tchapmi, M. (TA)
;
Tchapmi P., L. (TA)
;
Verma, S. (TA)
;
Wang, R. (TA)
;
Wornow, M. (TA)
;
Yang, S. (TA)
;
Zhang, P. (TA)
;
Zhang, T. (TA)
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