A Case Study on Improving Defense Behavior in Soccer Simulation 2D: The NeuroHassle Approach

Author:

Gabel Thomas,Riedmiller Martin,Trost Florian

Publisher

Springer Berlin Heidelberg

Cited by 11 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Deep Reinforcement Learning for Humanoid Robot Behaviors;Journal of Intelligent & Robotic Systems;2022-04-27

2. Contextual Bandit Learning With Reward Oracles and Sampling Guidance in Multi-Agent Environments;IEEE Access;2021

3. Deep Reinforcement Learning for Humanoid Robot Dribbling;2020 Latin American Robotics Symposium (LARS), 2020 Brazilian Symposium on Robotics (SBR) and 2020 Workshop on Robotics in Education (WRE);2020-11-09

4. Structure-Preserving Imitation Learning With Delayed Reward: An Evaluation Within the RoboCup Soccer 2D Simulation Environment;Frontiers in Robotics and AI;2020-09-16

5. Online Opponent Formation Identification Based on Position Information;RoboCup 2017: Robot World Cup XXI;2018

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