首页|Findings from Northwestern Polytechnic University Update Knowledge of Robotics ( Episode-fuzzy-coach Method for Fast Robot Skill Learning)

Findings from Northwestern Polytechnic University Update Knowledge of Robotics ( Episode-fuzzy-coach Method for Fast Robot Skill Learning)

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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – A new study on Robotics is now availab le. According to news reporting from Xi’an, People’s Republic of China, by NewsR x journalists, research stated, “To realize robot skill learning in the real wor ld, reinforcement learning algorithms need to be applied in continuous problems with high sample efficiency. Hybrid intelligence is regarded as an available sol ution for this problem, due to the ability to speed up the learning process with human knowledge and experience.” Financial support for this research came from National Natural Science Foundatio n of China (NSFC). The news correspondents obtained a quote from the research from Northwestern Pol ytechnic University, “Therefore, we propose Episode-Fuzzy-COACH (COrrective Advi ce Communicated by Humans), to imitate human fuzzy logic and involve human intel ligence in the learning process. In this framework, human knowledge and experien ce are involved in the learning process, which are provided by human feedback an d fuzzy rules designed by human users. Moreover, it is combined with Path Integr als Policy Improvement ( PI2 ), to realize hybrid intelligence, which is used to realize fast robot skill learning. Throwing Movement Primitives proposed in thi s article is used to represent the policy of ball-throwing skill. According to t he simulation results, the learning efficiency of our method is increased by 72% and 42.86%, respectively, compared with pure PI2 and PI2+ COACH. Ou r method validated in experiments is 46.67% more effective than PI 2+ COACH. The results also show that the performance of our method is not affect ed by users’ knowledge level of the related field.”

Xi’anPeople’s Republic of ChinaAsiaEmerging TechnologiesMachine LearningRobotRoboticsNorthwestern Polytech nic University

2024

Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
年,卷(期):2024.(Jun.4)