Hierarchical reinforcement learning of multiple grasping strategies with human instructions
Sign Up to like & getrecommendations! Published in 2018 at "Advanced Robotics"
DOI: 10.1080/01691864.2018.1509018
Abstract: ABSTRACT Grasping is an essential component for robotic manipulation and has been investigated for decades. Prior work on grasping often assumes that a sufficient amount of training data is available for learning and planning robotic… read more here.
Keywords: grasp; reinforcement learning; multiple grasping; hierarchical reinforcement ... See more keywords
Planning-Augmented Hierarchical Reinforcement Learning
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Robotics and Automation Letters"
DOI: 10.1109/lra.2021.3071062
Abstract: Planning algorithms are powerful at solving long-horizon decision-making problems but require that environment dynamics are known. Model-free reinforcement learning has recently been merged with graph-based planning to increase the robustness of trained policies in state-space… read more here.
Keywords: augmented hierarchical; reinforcement learning; reinforcement; hierarchical reinforcement ... See more keywords
A Task-Agnostic Regularizer for Diverse Subpolicy Discovery in Hierarchical Reinforcement Learning
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Systems, Man, and Cybernetics: Systems"
DOI: 10.1109/tsmc.2022.3209070
Abstract: The automatic subpolicy discovery approach in hierarchical reinforcement learning (HRL) has recently achieved promising performance on sparse reward tasks. This accelerates transfer learning and unsupervised intelligent creatures while eliminating the domain-specific knowledge constraint. Most previously… read more here.
Keywords: reinforcement learning; hierarchical reinforcement; subpolicy; subpolicy discovery ... See more keywords
Hierarchical Reinforcement Learning, Sequential Behavior, and the Dorsal Frontostriatal System
Sign Up to like & getrecommendations! Published in 2022 at "Journal of Cognitive Neuroscience"
DOI: 10.1162/jocn_a_01869
Abstract: Abstract To effectively behave within ever-changing environments, biological agents must learn and act at varying hierarchical levels such that a complex task may be broken down into more tractable subtasks. Hierarchical reinforcement learning (HRL) is… read more here.
Keywords: behavior; reinforcement learning; reinforcement; hierarchical reinforcement ... See more keywords