An example of the agent and environment dichotomy. This figure illustrates a robot taking actions that affect the state of the environment then receiving percepts with new information on the environment. (Image courtesy of Beryl Simon.)
for this course provides the topics for the course, along with direct links to lecture notes, homework assignments, and exams.
6.825 is a graduate-level introduction to artificial intelligence. Topics covered include: representation and inference in first-order logic, modern deterministic and decision-theoretic planning techniques, basic supervised learning methods, and Bayesian network inference and learning.
This course was also taught as part of the Singapore-MIT Alliance (SMA) programme as course number SMA 5504 (Techniques in Artificial Intelligence).
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