A Crash Course on Reinforcement Learning

Autor:	Yaghmaie, Farnaz Adib, Ljung, Lennart
Rok vydání:	2021
Předmět:	Computer Science - Machine Learning Electrical Engineering and Systems Science - Systems and Control
Druh dokumentu:	Working Paper
Popis:	The emerging field of Reinforcement Learning (RL) has led to impressive results in varied domains like strategy games, robotics, etc. This handout aims to give a simple introduction to RL from control perspective and discuss three possible approaches to solve an RL problem: Policy Gradient, Policy Iteration, and Model-building. Dynamical systems might have discrete action-space like cartpole where two possible actions are +1 and -1 or continuous action space like linear Gaussian systems. Our discussion covers both cases. Comment: https://github.com/FarnazAdib/Crash_course_on_RL
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2103.04910 Zobrazit plný text záznamu View this record from Arxiv