Advancements in Deep Reinforcement Learning and Inverse Reinforcement Learning for Robotic Manipulation: Toward Trustworthy, Interpretable, and Explainable Artificial Intelligence

Advancements in Deep Reinforcement Learning and Inverse Reinforcement Learning for Robotic Manipulation: Toward Trustworthy, Interpretable, and Explainable Artificial Intelligence

This article presents a literature review of the past five years of studies using Deep Reinforcement Learning (DRL) and Inverse Reinforcement Learning (IRL) in robotic manipulation tasks. The reviewed articles are examined in various categories, including DRL and IRL for perception, assembly, manipu...

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Bibliographic Details
Main Authors: Recep Ozalp, Aysegul Ucar, Cuneyt Guzelis
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Deep reinforcement learning
inverse reinforcement learning
robotic manipulation
artificial intelligence
trustworthy AI
interpretable AI
Online Access:https://ieeexplore.ieee.org/document/10493015/

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