References - shivamvats/notes GitHub Wiki

• Algorithms for Optimization: Mykel Kochenderfer's book; uses Julia.
• Greate references in my Dropbox folder

• Introduction to RL: chapter 8. Compares RL with other tabular (DP) methods including heuristic search.
• Model-based vs Model-free RL: https://medium.com/@jonathan_hui/rl-model-based-reinforcement-learning-3c2b6f0aa323

• Optimization and Optimal Control: Borrelli (Dropbox)
• Calculus of Variations and Optimal Control: Liberzon (Dropbox)

• Conjugate Priors: https://en.wikipedia.org/wiki/Conjugate_prior
• Bayesian Inference: https://personal.vu.nl/a.f.de.vos/primer/primer.pdf

• Abstract DP: http://web.mit.edu/dimitrib/www/abstractdp_MIT.html (Dropbox)

• Behavior-based Robotics: - Ronald Arkin. A mine-field of references and good quotes.
• Deepmind's AI Reading-List

• Manuel Blum's advice to graduate students.
• Collection of advice for PhD-students.
• Richard Hamming's - You and Your Research[1].