Structure-Preserving Imitation Learning With Delayed Reward: An Evaluation Within the RoboCup Soccer 2D Simulation Environment

Structure-Preserving Imitation Learning With Delayed Reward: An Evaluation Within the RoboCup Soccer 2D Simulation Environment

We describe and evaluate a neural network-based architecture aimed to imitate and improve the performance of a fully autonomous soccer team in RoboCup Soccer 2D Simulation environment. The approach utilizes deep Q-network architecture for action determination and a deep neural network for parameter...

Full description

Bibliographic Details
Main Authors: Quang Dang Nguyen, Mikhail Prokopenko
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-09-01
Series:Frontiers in Robotics and AI
Subjects:
deep learning
imitation learning
end-to-end learning
learning with structure preservation
learning with delayed reward
deep reinforcement learning
Online Access:https://www.frontiersin.org/article/10.3389/frobt.2020.00123/full

Internet

https://www.frontiersin.org/article/10.3389/frobt.2020.00123/full

Similar Items