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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Bibliografske podrobnosti

Principais autores:	Alberto del Rio, David Jimenez, Javier Serrano
Format:	Artigo
Jezik:	Inglês
Izdano:	IEEE 2024-01-01
Serija:	IEEE Access
Teme:	A3C CartPole comparison environment complexity Lunar Lander performance analysis
Online dostop:	https://ieeexplore.ieee.org/document/10703056/
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