| Lecture Title | Download PowerPoint | Download PDF | Note | |
|---|---|---|---|---|
| 1 | Introduction to Autonomy and Decision Making | Link to ppt | Link to pdf | |
| 2 | Modeling and Uninformed Search | Link to ppt | Link to pdf | |
| 3 | Path Planning as Informed Search | Link to ppt | Link to pdf | |
| 4 | Activity Planning as Heuristic Search | Link to ppt | Link to pdf | |
| 5 | Adversarial Games and Alpha-Beta Search | Link to ppt | Link to pdf | |
| 6 | Markov Decision Processes | Link to ppt | Link to pdf | |
| 7 | Probabilistic Planning | Link to ppt | Link to pdf | |
| 8 | Hidden Markov Models | Link to ppt | Link to pdf | |
| 9 | Propositional Logic: Satisfiability and Entailment | Link to ppt | Link to pdf | |
| 10 | Combining Propositional Inference and Search | Link to ppt | Link to pdf | |
| 11A | Sampling Based Path Planning | Link to ppt | Link to pdf | |
| 11B | Monte Carlo Tree Search | Link to ppt | Link to pdf | |
| 12 | Self-Repairing Systems | Link to ppt | Link to pdf | |
| 13 | Conflict-Directed Search | Link to ppt | Link to pdf | |
| 14 | Constraint Programs and Propagation | Link to ppt | Link to pdf | |
| 15 | Vehicle Routing as Constraint Programs | Link to ppt | Link to pdf | |
| 16 | Solving Constraint Problems with Search and Elimination | Link to ppt | Link to pdf | |
| 17 | Autonomous Ocean Exploration | Link to ppt | Not available | Guest lecture by Rich Camilli (WHOI) |
| 18 | Bayes Nets 1: Exact Inference | Link to ppt | Link to pdf | |
| 19 | Baytes Nets 2: Approximate Inference | Link to ppt | Link to pdf | |
| 20 | Temporal Networks | Link to ppt | Link to pdf | |
| 21 | Mathematical Programming: Modeling, Elimination and Intuitions | Link to ppt | Not available | |
| 22 | Linear Programming: Simplex Method | Link to ppt | Link to pdf | |
| 23 | Mixed Integer Programming with Branch and Bound | Link to ppt | Link to pdf | |
| 24 | Introduction to Convex Optimization | Link to ppt | Link to pdf | Guest Lecture by Simon Fang (Mobi) |
| 25-26 | Risk-Bounded Planning | Link to ppt | Link to pdf | |
| 27A | Course Review | Link to ppt | Link to pdf | |
| 27B | Course Highlights | Link to ppt | Link to pdf | Supplemental to the Course Review |
Theme: Multi-Agent Planning
| Lecture Title | Download PowerPoint | Download PDF | Jupyter Notebook | Note | |
|---|---|---|---|---|---|
| 1 | From POMDP to DecPOMDB | Link to ppt | Link to pdf | Link to notebook | Advanced Lecture by students |
| 2 | Non-Cooperative Games | Link to ppt | Link to pdf | Link to notebook | Advanced Lecture by students. FYI the notebook may not be working |
| 3 | Trust in Human-Robot Collaboration | Link to ppt | Link to pdf | Link to notebook | Advanced Lecture by students. FYI the notebook will not run in JupyterLite. Download "2022S-advanced-lecture-trust-human-robot/" and run locally instead |
| 4 | Applications of Epistemic Logic in Planning | Link to ppt | Link to pdf | Link to notebook | Advanced Lecture by students. FYI the notebook will not run in JupyterLite. Download "2022S-advanced-lecture-epistemic-logic-planning/" and run locally instead |
| 5 | Multi-Agent Prediction in Autonomous Driving | Link to ppt | Link to pdf | Link to notebook | Advanced Lecture by students. FYI the notebook will not run in JupyterLite. Download "2022S-advanced-lecture-ma-prediction-driving/" and run locally instead |
Theme: Planetary Exploration
| Lecture Title | Download PowerPoint | Download PDF | Jupyter Notebook | Note | |
|---|---|---|---|---|---|
| 1 | Adaptive Sampling | Link to ppt | Link to pdf | Link to notebook | Advanced Lecture by students |
| 2 | Semantic Segmentation | Link to ppt | Link to pdf | Link to notebook | Advanced Lecture by students. FYI the notebook will not run in JupyterLite. Download "2020S-advanced-lecture-2-semantic-segmentation/" and run locally instead |
| 3 | Decentralized Planning | Link to ppt | Link to pdf | Link to notebook | Advanced Lecture by students. FYI the notebook may not be working |
| 4 | Intent Recognition | Link to ppt | Link to pdf | Link to notebook | Advanced Lecture by students. FYI the notebook will not run in JupyterLite. Download "2022S-advanced-lecture-epistemic-logic-planning/" and run locally instead |