Comprehensive Overview of Reward Engineering and Shaping in Advancing Reinforcement Learning Applications

Reinforcement Learning (RL) seeks to develop systems capable of autonomous decision-making by learning through interaction with their environment. Central to this process are reward engineering and reward shaping, which are essential for enhancing the efficiency and effectiveness of RL algorithms. T...

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Bibliographic Details
Main Authors: Sinan Ibrahim, Mostafa Mostafa, Ali Jnadi, Hadi Salloum, Pavel Osinenko
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/10763475/
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