Motivation

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!

Optimization and Optimal Control

• “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

Game Theory

• 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.
• Smooth Game Theory by David Fridovich-Keil provides a great overview of smooth static and dynamic games that commonly arise in motion planning and control problems. This book is a great entry point for readers that have a background in (single-player) optimization and appreciate a presentation style akin to that of Nocedal & Wright.
• 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.
• Multi-Agent Reinforcement Learning: A Selective Overview of Theories and Algorithms provides a great overview of multi-agent reinforcement learning narrated from the perspective of traditional game theory.

Programming & Essential Tools

• 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
  • Beginneres guide to git
  • Git tutorial from MIT’s “missing semester”-class
  • Interactive Git tutorial
• Julia:
  • Getting Started (Julia Docs)
  • JuliaNotes.jl: A collection of examples and explanations about Julia (development workflows etc.)
  • JuliaAcademy free course overview
• C++
  • Modern C++ course by IPB
  • Modern CMake online book
• Python
  • Full Stack Python
• Robot Operating System (ROS)
  • YouTube Lecture on ROS by Peter Frankenhauser
  • ROS Tutorial Website

Miscellaneous Mathematical Foundations

• Marc Toussaint’s lecture notes on “Maths for Intelligent Systems”
• The Mechanics of Proofs
• Proofs and Fundamentals, A First Course in Abstract Mathematics by Ethan Bloch
• 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

Softskills

• 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