Behavior policy learning: Learning multi-stage tasks via solution sketches and model-based controllers

Behavior policy learning: Learning multi-stage tasks via solution sketches and model-based controllers

Multi-stage tasks are a challenge for reinforcement learning methods, and require either specific task knowledge (e.g., task segmentation) or big amount of interaction times to be learned. In this paper, we propose Behavior Policy Learning (BPL) that effectively combines 1) only few solution sketche...

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Bibliographic Details
Main Authors: Konstantinos Tsinganos, Konstantinos Chatzilygeroudis, Denis Hadjivelichkov, Theodoros Komninos, Evangelos Dermatas, Dimitrios Kanoulas
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-10-01
Series:Frontiers in Robotics and AI
Subjects:
imitation learning
multi-stage tasks
evolutionary strategies
reinforcement learning
sim2real
Online Access:https://www.frontiersin.org/articles/10.3389/frobt.2022.974537/full

Internet

https://www.frontiersin.org/articles/10.3389/frobt.2022.974537/full

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