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ym-book.tex
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\documentclass[12pt]{book}
\usepackage{graphicx,ae}
\usepackage{color}
\usepackage{amsmath}
\usepackage{amssymb}
% \usepackage{hyperref}
\usepackage{fullpage}
\usepackage{natbib}
\usepackage{framed}
\newcommand{\ymignore}[1]{}
\usepackage{hyperref}
\input{defs}
\title{Reinforcement Learning: Foundations}
\date{February 2023
\\
\textcolor{red}{This book is still work in progress. In particular, references to literature are not complete. We would be grateful for comments, suggestions, omissions, and errors of any kind, at \url{rlfoundationsbook@gmail.com}. }
}
\author{Shie Mannor, Yishay Mansour and Aviv Tamar}
\newcommand{\shie}[1]{\textcolor{blue}{#1}}
\begin{document}
\maketitle
\tableofcontents
\chapter{Introduction and Overview}
\label{chapter:intro}
\input{current_chapters/chapter1-intro}
\chapter{Deterministic Decision Processes}
\label{chapter:DDP}
\input{current_chapters/chapter2-ddp}
\chapter{Markov Chains}
\label{chapter:MC}
\input{current_chapters/chapter3-mc}
\chapter{Markov Decision Processes and Finite Horizon Dynamic Programming}
\label{chapter:MDP-FH}
\input{current_chapters/chapter4-mdp-fh}
\chapter{Discounted Markov Decision Processes}
\label{chapter:disc}
\input{current_chapters/chapter5-disc}
\chapter{Linear Programming Solutions}\label{chapter-LP}
\input{current_chapters/LP}
\chapter{Reinforcement Learning: Model Based}\label{chapter-model-based}
\input{current_chapters/chapter6-mbrl}
\chapter{Reinforcement Learning: Model Free}
\label{chapter:learning-model-free}
\input{old_stuff/chapter7-mfrl1}
\newpage
\input{old_stuff/chapter7-mfrl2}
\chapter{Large State Spaces: Value Function Approximation}
\label{chapter:function-approximation}
\input{current_chapters/chapter8-fa}
\chapter{Large State Space: Policy Gradient Methods}
\label{chapter:policy-gradient}
\input{old_stuff/chapter9-pg}
\chapter{ Multi-Arm bandits}
\label{chapter:MAB}
\input{current_chapters/chapter10-mab}
\chapter{POMDP}
\label{chapter:POMDP}
\input{ym_chapters/Lecture-POMDP}
\chapter{LQR}
\label{chapter:LQR}
\input{ym_chapters/Lecture-LQR}
\chapter{Generative Model}
\label{chapter:generative}
\input{ym_chapters/Lecture-Generative}
\chapter{Inverse RL and Apprenticeship learning}
\label{chapter:IRL}
\input{ym_chapters/Lecture-IRL}
\appendix
\chapter{Dynamic Programming}
\label{chapter:dp}
\input{current_chapters/appendix-dp}
% \chapter{Approximate Dynamic Programming}
% \label{chapter:approx-dp}
% %\input{future_chapters/Lecture-ApproximateDP_Aviv}
% \input{current_chapters/chapter8-fa}
\bibliographystyle{plain}
\bibliography{bib-lecture}
\end{document}