Comparison of Multiple Reinforcement Learning and Deep Reinforcement Learning Methods for the Task Aimed at Achieving the Goal

Comparison of Multiple Reinforcement Learning and Deep Reinforcement Learning Methods for the Task Aimed at Achieving the Goal

Reinforcement Learning (RL) and Deep Reinforcement Learning (DRL) methods are a promising approach to solving complex tasks in the real world with physical robots. In this paper, we compare several reinforcement  learning (Q-Learning, SARSA) and deep reinforcement learning (Deep Q-Network, Deep Sar...

Full description

Bibliographic Details
Main Authors: Roman Parak, Radomil Matousek
Format: Article
Language:English
Published: Brno University of Technology 2021-06-01
Series:Mendel
Subjects:
Reinforcement Learning
Deep neural network
Motion planning
Bézier spline
Robotics
UR3
Online Access:https://mendel-journal.org/index.php/mendel/article/view/132

Internet

https://mendel-journal.org/index.php/mendel/article/view/132

Similar Items