73 citations · 133 across the 11 of their papers we have counts for
11 papers
Optimistic Model Rollouts for Pessimistic Offline Policy Optimization
Yuanzhao Zhai, Yiying Li, Zijian Gao +5
Model-based offline reinforcement learning (RL) has made remarkable progress, offering a promising avenue for improving generalization with synthetic model rollouts. Existing works…
Dynamic Memory-based Curiosity: A Bootstrap Approach for Exploration
Zijian Gao, YiYing Li, Kele Xu +5
The sparsity of extrinsic rewards poses a serious challenge for reinforcement learning (RL). Currently, many efforts have been made on curiosity which can provide a representative…
Nuclear Norm Maximization Based Curiosity-Driven Learning
Chao Chen, Zijian Gao, Kele Xu +5
To handle the sparsity of the extrinsic rewards in reinforcement learning, researchers have proposed intrinsic reward which enables the agent to learn the skills that might come in…
A Fixed Version of Quadratic Program in Gradient Episodic Memory
Wei Zhou, Yiying Li
Gradient Episodic Memory is indeed a novel method for continual learning, which solves new problems quickly without forgetting previously acquired knowledge. However, in the proces…
KnowSR: Knowledge Sharing among Homogeneous Agents in Multi-agent Reinforcement Learning
Zijian Gao, Kele Xu, Bo Ding +3
Recently, deep reinforcement learning (RL) algorithms have made great progress in multi-agent domain. However, due to characteristics of RL, training for complex tasks would be res…
KnowRU: Knowledge Reusing via Knowledge Distillation in Multi-agent Reinforcement Learning
Zijian Gao, Kele Xu, Bo Ding +3
Recently, deep Reinforcement Learning (RL) algorithms have achieved dramatically progress in the multi-agent area. However, training the increasingly complex tasks would be time-co…
FedH2L: Federated Learning with Model and Statistical Heterogeneity
Yiying Li, Wei Zhou, Huaimin Wang +2
Federated learning (FL) enables distributed participants to collectively learn a strong global model without sacrificing their individual data privacy. Mainstream FL approaches req…
Online Meta-Critic Learning for Off-Policy Actor-Critic Methods
Wei Zhou, Yiying Li, Yongxin Yang +2
Off-Policy Actor-Critic (Off-PAC) methods have proven successful in a variety of continuous control tasks. Normally, the critic's action-value function is updated using temporal-di…
Attention-based Fault-tolerant Approach for Multi-agent Reinforcement Learning Systems
Mingyang Geng, Kele Xu, Yiying Li +3
The aim of multi-agent reinforcement learning systems is to provide interacting agents with the ability to collaboratively learn and adapt to the behavior of other agents. In many…
Feature Fusion Detector for Semantic Cognition of Remote Sensing
Wei Zhou, Yiying Li
The value of remote sensing images is of vital importance in many areas and needs to be refined by some cognitive approaches. The remote sensing detection is an appropriate way to…
Feature-Critic Networks for Heterogeneous Domain Generalization
Yiying Li, Yongxin Yang, Wei Zhou +1
The well known domain shift issue causes model performance to degrade when deployed to a new target domain with different statistics to training. Domain adaptation techniques allev…