cs323-notes
These notes are based on Stanford CS323, taught by Stefano Ermon, and have been written by Michael Zhu.
This course is a graduate level introduction to automated reasoning techniques and their applications, covering logical and probabilistic approaches. Topics include: logical and probabilistic foundations, backtracking strategies and algorithms behind modern SAT solvers, stochastic local search and Markov Chain Monte Carlo algorithms, classes of reasoning tasks and reductions, and applications.
The compiled version is available here.
Contributing
The notes are still under construction! If you find any typos or can contribute to help make the notes better, please let us know, or submit a pull request with your fixes via Github.
The notes are written in Markdown and are compiled into HTML using Jekyll. Please add your changes directly to the Markdown source code.