中文版 | English

在结果中检索

CASIA OpenIR
（本次检索基于用户作品认领结果）

浏览/检索结果: 共14条，第1-10条 帮助

限定条件            
已选(0)清除 条数/页：   排序方式：
Soft Contrastive Learning with Q-irrelevance Abstraction for Reinforcement Learning 期刊论文
IEEE Transactions on Cognitive and Developmental Systems, 2023, 卷号: 15, 期号: 3, 页码: 1463 - 1473
作者:  Liu MS(刘民颂);  Li LT(李伦通);  Hao S(郝帅);  Zhu YH(朱圆恒);  Zhao DB(赵冬斌)
Adobe PDF(4197Kb)  |  收藏  |  浏览/下载：18/3  |  提交时间：2024/06/24
Deep Reinforcement Learning-Based Driving Policy at Intersections Utilizing Lane Graph Networks 期刊论文
IEEE Transactions on Cognitive and Developmental Systems, 2024, 页码: 1 - 16
作者:  Liu, Yuqi;  Zhang, Qichao;  Gao, Yinfeng;  Zhao, Dongbin
Adobe PDF(22863Kb)  |  收藏  |  浏览/下载：22/6  |  提交时间：2024/06/03
Reinforcement Learning  Autonomous Driving  Intersection Navigating  
Multi-task safe reinforcement learning for navigating intersections in dense traffic 期刊论文
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS, 2023, 卷号: 360, 期号: 17, 页码: 13737-13760
作者:  Liu, Yuqi;  Gao, Yinfeng;  Zhang, Qichao;  Ding, Dawei;  Zhao, Dongbin
Adobe PDF(3095Kb)  |  收藏  |  浏览/下载：68/9  |  提交时间：2024/02/22
Online Minimax Q Network Learning for Two-Player Zero-Sum Markov Games 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2022, 卷号: 33, 期号: 3, 页码: 1228-1241
作者:  Zhu, Yuanheng;  Zhao, Dongbin
Adobe PDF(2838Kb)  |  收藏  |  浏览/下载：233/4  |  提交时间：2022/06/10
Games  Nash equilibrium  Mathematical model  Markov processes  Convergence  Dynamic programming  Training  Deep reinforcement learning (DRL)  generalized policy iteration (GPI)  Markov game (MG)  Nash equilibrium  Q network  zero sum  
Highway Lane Change Decision-Making via Attention-Based Deep Reinforcement Learning 期刊论文
IEEE-CAA JOURNAL OF AUTOMATICA SINICA, 2022, 卷号: 9, 期号: 3, 页码: 567-569
作者:  Wang, Junjie;  Zhang, Qichao;  Zhao, Dongbin
Adobe PDF(803Kb)  |  收藏  |  浏览/下载：283/66  |  提交时间：2022/02/16
BNAS-v2: Memory-efficient and Performance-collapse-prevented Broad Neural Architecture Search 期刊论文
IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS: SYSTEMS, 2022, 卷号: 0, 期号: 0, 页码: 0
作者:  Zixiang, Ding;  Yaran, Chen;  Nannan, Li;  Dongbin, Zhao
Adobe PDF(7657Kb)  |  收藏  |  浏览/下载：218/56  |  提交时间：2022/01/07
Broad neural architecture search (BNAS), continuous relaxation, confident learning rate, partial channel connections, image classification.  
BNAS: Efficient Neural Architecture Search Using Broad Scalable Architecture 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2020, 期号: 0, 页码: 0
作者:  Ding ZX(丁子祥);  Yaran, Chen;  Nannan, Li;  Dingbin, Zhao;  Zhiquan, Sun;  C. L. Philip Chen
Adobe PDF(2713Kb)  |  收藏  |  浏览/下载：194/45  |  提交时间：2022/01/06
Broad convolutional neural network (BCNN), image classification, neural architecture search (NAS), reinforcement learning (RL)  
Enhanced Rolling Horizon Evolution Algorithm With Opponent Model Learning: Results for the Fighting Game AI Competition 期刊论文
IEEE TRANSACTIONS ON GAMES, 2023, 卷号: 5, 期号: 1, 页码: 5 - 15
作者:  Zhentao Tang;  Yuanheng Zhu;  Dongbin Zhao;  Simon M. Lucas
Adobe PDF(7686Kb)  |  收藏  |  浏览/下载：325/69  |  提交时间：2021/07/05
Rolling horizon evolution  opponent model  reinforcement learning  supervised learning  fighting game  
MGRL: Graph neural network based inference in a Markov network with Reinforcement Learning for visual navigation 期刊论文
Neurocomputing, 2021, 卷号: 0, 期号: 0, 页码: 0
作者:  Lu, Yi;  Chen, Yaran;  Zhao, Dongbin;  Li, Dong
浏览  |  Adobe PDF(976Kb)  |  收藏  |  浏览/下载：271/78  |  提交时间：2020/10/19
Visual navigation, graph neural network, Markov network, reinforcement learning, probabilistic graph model  
Deep Reinforcement Learning-Based Automatic Exploration for Navigation in Unknown Environment 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2020, 卷号: 31, 期号: 6, 页码: 2064-2076
作者:  Li, Haoran;  Zhang, Qichao;  Zhao, Dongbin
浏览  |  Adobe PDF(4274Kb)  |  收藏  |  浏览/下载：397/121  |  提交时间：2020/08/03
Robot sensing systems  Navigation  Entropy  Neural networks  Task analysis  Planning  Automatic exploration  deep reinforcement learning (DRL)  optimal decision  partial observation