Comparative Analysis of A3C and PPO Algorithms in Reinforcement Learning: A Survey on General Environments

Comparative Analysis of A3C and PPO Algorithms in Reinforcement Learning: A Survey on General Environments

This research article presents a comparison between two mainstream Deep Reinforcement Learning (DRL) algorithms, Asynchronous Advantage Actor-Critic (A3C) and Proximal Policy Optimization (PPO), in the context of two diverse environments: CartPole and Lunar Lander. DRL algorithms are widely known fo...

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Bibliographic Details
Main Authors: Alberto del Rio, David Jimenez, Javier Serrano
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
A3C
CartPole
comparison
environment complexity
Lunar Lander
performance analysis
Online Access:https://ieeexplore.ieee.org/document/10703056/
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