2. Markov Decision Processes and Bellman Equations
Overview
This chapter will cover more of the theory behind reinforcement learning. We will cover Markov chains, Markov reward processes, and Markov decision processes. We will learn about the concepts of state values and action values along with Bellman equations to calculate previous quantities. By the end of this chapter, you will be able to solve Markov decision processes using linear programming methods.
推薦閱讀
- Intel FPGA/CPLD設(shè)計(jì)(基礎(chǔ)篇)
- Istio入門與實(shí)戰(zhàn)
- 嵌入式技術(shù)基礎(chǔ)與實(shí)踐(第5版)
- The Applied AI and Natural Language Processing Workshop
- Mastering Manga Studio 5
- 筆記本電腦維修不是事兒(第2版)
- 微型計(jì)算機(jī)系統(tǒng)原理及應(yīng)用:國(guó)產(chǎn)龍芯處理器的軟件和硬件集成(基礎(chǔ)篇)
- Source SDK Game Development Essentials
- Spring Cloud實(shí)戰(zhàn)
- Spring Security 3.x Cookbook
- 單片機(jī)原理與技能訓(xùn)練
- FreeSWITCH Cookbook
- Zabbix 4 Network Monitoring
- 基于S5PV210處理器的嵌入式開發(fā)完全攻略
- The Machine Learning Workshop