This repository accompanies Reinforcement Learning for Sequential Decision and Optimal Control by Shengbo Eben Li (SpringerNature, 2023).
Download the files as a zip using the green button, or clone the repository to your machine using Git.
Release v1.0 corresponds to the code in the published book, without corrections or updates.
Setup conda first, and install dependencies.
conda env create -n rlbook -f environment.yml
conda activate rlbook
Then open each folder and run main
or plot
Python script.
Chap_3_4_CleanRobot
: Code for robot cleaning example in Chapter 3 and 4.Chap_5_AutoCar_GridRoad
: Code for autonomous car example in Chapter 5.Chap_6_Actor_Critic_Algorithm
: Code for actor-critic algorithm in Chapter 6.Chap_7_AC_wtih_Baseline
: Code for AC algorithm with baseline comparison in Chapter 7.Chap_8_Veh_Track_Ctrl
: Code for vehicle tracking control example in Chapter 8.Chap_9_Car_Brake_Control
: Code for emergency braking control example in Chapter 9.
See the file Contributing.md for more information on how you can contribute to this repository.