If you need help please check the discussion board on Canvas!. We check it regularly to answer common questions on projects and homeworks. The solution to your question might already be there!
There are a few AI books online that provide additional explanations and examples. These are generally free and open to download.
- Artificial Intelligence 2E by David L. Poole and Alan K. Mackworth. This book also has a great set of online resources and algorithm animations AI Space.
- A list of other books including some good free books on Machine Learning..
- Sutton and Barto Book on Reinforcement Learning
Links to other versions of this course and additional reading. I have borrowed liberally from many of these versions of the course and have provided these sources to help students.
- Anca Dragan’s Course at UC Berkeley Fall 2019 Fall 2020
- Dan Klein and Peter Abbeel’s older course at UC Berkeley and Fall 2018 Version
- Subbarao Kambhampati’s Course at ASU Fall 2019
- Maria Gini’s Course at UMN 2018
- Peter Stone’s Course at UT Austin Fall 2017
- Vincent Conitzer’s Course at Duke Spring 2019
- Lirong Xia’s Course at RPI Spring 2020
- Yair Zick’s Course at NUS
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Also thanks to Prof. K. Brent Venable and Prof. Jihun Hamm for sharing their versions of this course with me.
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UC Santa Barbra Yu-Xiang Wang
- Gurobi Notebooks