1 code implementation • 25 Jul 2021 • Junjie Li, Jingyao Li, Wenbo Zhou, Shuai Lü
The training of generative adversarial networks (GANs) is usually vulnerable to mode collapse and vanishing gradients.
1 code implementation • 27 Jan 2021 • Junjie Li, Junwei Zhang, Xiaoyu Gong, Shuai Lü
Generative Adversarial Networks (GAN) is an adversarial model, and it has been demonstrated to be effective for various generative tasks.
no code implementations • 11 Nov 2020 • Junwei Zhang, Zhenghao Zhang, Shuai Han, Shuai Lü
Based on continuous control tasks with dense reward, this paper analyzes the assumption of the original Gaussian action exploration mechanism in PPO algorithm, and clarifies the influence of exploration ability on performance.
no code implementations • 1 Jul 2020 • Shuai Han, Wenbo Zhou, Shuai Lü, Jiayu Yu
Deep Deterministic Policy Gradient (DDPG) algorithm is one of the most well-known reinforcement learning methods.
no code implementations • 19 Jun 2020 • Shuai Han, Wenbo Zhou, Jing Liu, Shuai Lü
Effective exploration for noisy networks is one of the most important issues in deep reinforcement learning.
no code implementations • 13 Dec 2019 • Shuai Lü, Shuai Han, Wenbo Zhou, Junwei Zhang
In this paper, we propose Recruitment-imitation Mechanism (RIM) for evolutionary reinforcement learning, a scalable framework that combines advantages of the three methods mentioned above.