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There are no required textbooks for this course, but the following are good references:
- Planning with Markov Decision Processes: An AI Perspective. Mausam & Andrey Kolobov (Morgan & Claypool, 2012).
- Algorithms for Decision Making. Mykel J. Kochenderfer (MIT Press, 2022).
- Planning Algorithms. Steven M. LaValle (Cambridge University Press, 2006).
- Artificial Intelligence: A Modern Approach (AIMA). Stuart Russell & Peter Norvig (Fourth Edition, Pearson, 2020).
- Probabilistic Machine Learning: An Introduction. Kevin Murphy (MIT Press, 2022).
- Pattern Recognition and Machine Learning. Christopher Bishop (Springer, 2006).
- Reinforcement Learning: An Introduction. Richard Sutton & Andrew Barto (Second Edition, MIT Press, 2018).
- Machine Learning Methods for Planning. Steven Minton (Morgan Kaufmann, 2000).