====== Assignment #2 - Probabilistic Planner ====== /*Information below is from the last year. It is shown here to give you an idea of what to expect and plan accordingly. However, since we are working on improving the assignment in possibly non-trivial ways, **don't start working on the assignment until it gets handed out in tutorials!***/ Description of the assignment: {{ :courses:be4m36pui:assignments:tutassignment2.pdf | presentation}} Dataset: {{ :courses:pui:assignments:dataset-assignment2.zip |}} Submission deadline for tutor feedback (if you want it): **15. 5. 2023** Final submission deadline: **28. 5. 2023** Please report any issues with the assignment to [[mrkosja1@fel.cvut.cz]] for extra credit. ===== Submission instructions ===== Please submit your report together with any source code and README that describes how to run your simulations into BRUTE, as a single archive (zip, tar, tgz, bz2). If possible, please include the report in the top-level folder of the archive and name it ''report_YourCtuLogin.pdf''. If possible, save your report as ''.pdf''. Include your source codes in a subfolder of the archive. ===== Office hours to discuss assignment 2 ===== * We 25. 5., 13:00-14:00, KN:E-326 * Thu 26. 5. 13:00-14:00, KN:E-326 ===== Recommended resources ===== Please let me know if you run into issues accessing the following resources. Fundamentals: * Book: Russell, Stuart, and Peter Norvig. Artificial Intelligence: A Modern Approach. Third edition. Prentice Hall, 1995, chapter 17. Value iteration extensions: * Book: Mausam, and Andrey Kolobov. Planning with Markov Decision Processes: An AI Perspective, 2016, sections of chapter 3. Monte-Carlo Tree Search (UCT): * Online book: Kochenderfer, Mykel J., Tim A. Wheeler, and Kyle H. Wray. Algorithms for Decision Making. Cambridge, MA, USA: MIT Press, 2022, [[https://algorithmsbook.com/|https://algorithmsbook.com/]], section 9.6, pages 187-197 * Book: Mausam, and Andrey Kolobov. Planning with Markov Decision Processes: An AI Perspective, 2016, pages 111-113.