The goal of this document is to provide some initial pointers for anyone new to research in the regime of multi-agent interaction. Given my research interests, the resources focus on material from game theory, optimal control, and robot learning. I originally created this collection to accelerate the collaboration with new students but if you find these resources helpful for other contexts, please feel free to share them.

**Note:** If you have suggestions for additional resources or learning tools, please shoot me an email!

- “Numerical Optimization” book by Nocedal and Wright
- “Algorithms for Decision Making” book by Kochenderfer et al.
- “Algorithms for Optimization” book by Kochenderfer et al.
- “Predictive Control for Linear and Hybrid Systems” book by Borrelli et al.
- “Decision Makijng Under Uncertainty: Theory and Application”
- Underactuated Robotics by Russ Tedrake
- Dynamic programming and optimal control by Dimitri Bertsekas
- Introduction to the fundamentals of forward and reverse mode automatic differentiation
- “Calculus of Variations and Optimal Control Theory” by Daniel Liberzon

- Dynamic Noncooperative Game Theory by Başar and Olsder is essentially the bible on the topic of noncooperative games. It’s a bit hard to find online but I’m happy to borrow you my copy.
- Algorithmic Game Theory by Nisan et al. is similarly exhaustive but with a greater focus on discrete domains and language tailored towards a CS (rather than control) audience.
- Generalized Nash Equilibrium Problems by Facchinei and Kanzow provides a great overview on noncooperative games with
*constraints between players*, i.e. generalized Nash equilibrium problems (GNEPs). This theory is particularly interesting for constrained motion-planning settings. - Finite-dimensional variational inequalities and complementarity problems by Facchinei and Pang includes a thorough discussion of variational inequalities (VIs) which include the KKT systems resulting from GNEPs as a special case.
- The lecture notes on Game Theoretical Motion Planning from the ICRA 2021 tutorial provide a good introduction to applications of game-theory to the problem of motion planning.

- MIT’s class “The Missing Semester of Your CS Education” provides a solid background on essential tools ranging from “how to work with the shell”, over “how to work with git” to “how tow work build systems such as Make”.
- Git: Version control for your source code
- Julia:
- C++
- Python
- Robot Operating System (ROS)

- Marc Toussaint’s lecture notes on “Maths for Intelligent Systems”
- Mobile robotics basics: Online class by Cyrill Stachniss
- Linear Algebra Lecture by 3Blue1Brown
- MIT 18.06: Linear Algebra
- Essence of calculus by 3Blue1Brown
- Quaternions and 3D rotations explained by 3Blue1Brown
- “The Big Six Matrix Factorizations”
- Absolute Basics of robotics: YouTube Playlist: Probabilities, Coordinate Transformations

- Getting Things Done (GTD) workflow basics: YouTube Playlist
- “How to Write a Reserach Paper” by Microsoft Research
- “How to Speak” by Patrick Winston
- “Talks that Don’t Suck” by Cyrill Stachniss
- “Tips for Your First Conference Talk” by Cyrill Stachniss
- “What matters for your PhD Defense Talk” by Cyrill Satchniss