中文版 | English

在结果中检索

CASIA OpenIR

浏览/检索结果: 共5条，第1-5条 帮助

限定条件    
已选(0)清除 条数/页：   排序方式：
Deep Reinforcement Learning With Visual Attention for Vehicle Classification 期刊论文
IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS, 2017, 卷号: 9, 期号: 4, 页码: 356-367
作者:  Zhao, Dongbin;  Chen, Yaran;  Lv, Le
浏览  |  Adobe PDF(3192Kb)  |  收藏  |  浏览/下载：1017/535  |  提交时间：2017/05/08
Convolutional Neural Network (Cnn)  Reinforcement Learning  Vehicle Classification  Visual Attention  
Adaptive Critic Nonlinear Robust Control: A Survey 期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2017, 卷号: 47, 期号: 10, 页码: 3429-3451
作者:  Wang, Ding;  He, Haibo;  Liu, Derong
Adobe PDF(1954Kb)  |  收藏  |  浏览/下载：401/142  |  提交时间：2018/03/03
Adaptive Critic Designs  Adaptive/approximate Dynamic Programming (Adp)  Boundedness  Convergence  Neural Networks  Optimal Control  Reinforcement Learning  Robust Control  Stability  
FMRQ-A Multiagent Reinforcement Learning Algorithm for Fully Cooperative Tasks 期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2017, 卷号: 47, 期号: 6, 页码: 1367-1379
作者:  Zhang, Zhen;  Zhao, Dongbin;  Gao, Junwei;  Wang, Dongqing;  Dai, Yujie
收藏  |  浏览/下载：280/0  |  提交时间：2017/07/18
Multiagent Reinforcement Learning (Marl)  Nash Equilibrium  Q-learning  Repeated Game  
Off-Policy Integral Reinforcement Learning Method to Solve Nonlinear Continuous-Time Multiplayer Nonzero-Sum Games 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2017, 卷号: 28, 期号: 3, 页码: 704-713
作者:  Song, Ruizhuo;  Lewis, Frank L.;  Wei, Qinglai
收藏  |  浏览/下载：173/0  |  提交时间：2017/05/05
Adaptive Critic Designs  Adaptive Dynamic Programming (Adp)  Approximate Dynamic Programming  Integral Reinforcement Learning (Irl)  Nonlinear Systems  Nonzero Sum (Nzs)  Off-policy  
FMR-GA -- A cooperative multi-agent reinformcement learning algorithm based on gradient ascent 期刊论文
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10634), 2017, 期号: *, 页码: 840–848
作者:  Zhen Zhang;  Dongqing Wang;  Dongbin Zhao;  Tingting Song
收藏  |  浏览/下载：135/0  |  提交时间：2017/12/31
Reinforcement Learning  Multi-agent  Gradient Ascent  Q-learning