A Concise Introduction to Reinforcement Learning in Robotics

2022-10-13 · Akash Nagaraj, Mukund Sood, Bhagya M Patil

One of the biggest hurdles robotics faces is the facet of sophisticated and hard-to-engineer behaviors. Reinforcement learning offers a set of tools, and a framework to address this problem. In parallel, the misgivings of robotics offer a solid testing ground and evaluation metric for advancements in reinforcement learning. The two disciplines go hand-in-hand, much like the fields of Mathematics and Physics. By means of this survey paper, we aim to invigorate links between the research communities of the two disciplines by focusing on the work done in reinforcement learning for locomotive and control aspects of robotics. Additionally, we aim to highlight not only the notable successes but also the key challenges of the application of Reinforcement Learning in Robotics. This paper aims to serve as a reference guide for researchers in reinforcement learning applied to the field of robotics. The literature survey is at a fairly introductory level, aimed at aspiring researchers. Appropriately, we have covered the most essential concepts required for research in the field of reinforcement learning, with robotics in mind. Through a thorough analysis of this problem, we are able to manifest how reinforcement learning could be applied profitably, and also focus on open-ended questions, as well as the potential for future research.

📄 PDF Abstract BibTeX arXiv:2210.07397

Code (0)

등록된 구현이 없습니다.

Tasks

reinforcement-learning Reinforcement Learning Reinforcement Learning (RL)Survey

An Introduction to Deep Reinforcement Learning

2018-11-30 · Vincent Francois-Lavet, Peter Henderson, Riashat Islam, Marc G. Bellemare 외

Deep reinforcement learning is the combination of reinforcement learning (RL) and deep learning. This field of research has been able to solve a wide range of complex decision-making tasks that were previously out of rea…

BIG-bench Machine Learning Decision Making Deep Reinforcement Learning reinforcement-learning+2

Reinforcement Learning Applications

2019-08-19 · Yuxi Li

We start with a brief introduction to reinforcement learning (RL), about its successful stories, basics, an example, issues, the ICML 2019 Workshop on RL for Real Life, how to use it, study material and an outlook. Then …

Recommendation Systems reinforcement-learning Reinforcement Learning Reinforcement Learning (RL)

A Crash Course on Reinforcement Learning

2021-03-08 · Farnaz Adib Yaghmaie, Lennart Ljung

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 dis…

reinforcement-learning Reinforcement Learning Reinforcement Learning (RL)

A Practical Introduction to Deep Reinforcement Learning

2025-05-13 · Yinghan Sun, Hongxi Wang, Hua Chen, Wei zhang

Deep reinforcement learning (DRL) has emerged as a powerful framework for solving sequential decision-making problems, achieving remarkable success in a wide range of applications, including game AI, autonomous driving, …

Autonomous Driving Decision Making Deep Reinforcement Learning Diversity+3

Deep Robot Sketching: An application of Deep Q-Learning Networks for human-like sketching

2024-02-01 · Raul Fernandez-Fernandez, Juan G. Victores, Carlos Balaguer

The current success of Reinforcement Learning algorithms for its performance in complex environments has inspired many recent theoretical approaches to cognitive science. Artistic environments are studied within the cogn…

Q-Learning reinforcement-learning Reinforcement Learning