F. (2013). Simulation and managerial decision making: A double-loop learning framework. Public Admini stration Review, 73(2), 291-300.Kim, H.; MacDonald, R.H.; Andersen, D.F. Simulation and managerial decision making: A double-loop learning framework. Public Adm. Rev. 2013, doi:...
<a href=”https://www.toolshero.com/change-management/single-loop-learning/”>Toolshero: Single and double loop learning model</a>
An Extension of Weighted Strategy Sharing in Cooperative Q-Learning for Specialized Agents Eshgh, A. M. and Ahmadabadi, M. N. Proceedings of the 9th ... SM Eshgh,MN Ahmadabadi - IEEE 被引量: 17发表: 2002年 A cognitive framework for \\{WSN\\} based on weighted cognitive maps and Q-...
Double Deep Q-Network Next-Generation Cyber-Physical Systems: A Reinforcement Learning-Enabled Anomaly Detection Framework for Next-Generation Cyber-Physic... In this work, we considered the problem of anomaly detection in next-generation cyber-physical systems (NG-CPS). For this, we used a doubl...
This paper develops a framework for facilitating organizational learning through social media text analytics to enhance citizen-centric public service quality. Theoretically, the framework integrates double-loop learning theory with extant models of e-participation in government. Empirically, the framework is...
首先是原理上的对比，强化学习研究的目标是训练出一个对应于具体任务的好模型，这两个训练策略的方法是...
Finally, a deep temporal difference reinforcement learning framework is established, and a large number of comparative experiments are designed to analyze the basic performance of this algorithm. The results showed that the proposed algorithm was better than most other methods, which contributed to ...
\(q\in \{{{\rm {RNA}}},{{\rm {ADT}}},{{\rm {ATAC}}}\}\) denotes the indicator of modalities. \({X}_{{ij}}^{(q)}\) denotes the random variable that models the value of the ith stable feature (\(i=1,\ldots,{m}^{(q)}\)) of the jth droplet (\(j=1,\ldots,...
This paper extends therecently proposed weighted double estimator tothe multiagent domain and propose a multiagentDRL framework, named weighted double deep Q-network(WDDQN).Byutilizingtheweighteddou-ble estimator and the deep neural network, WD-DQN can not only reduce the bias effectively butalso ...
DoubleML: An Object-Oriented Implementation of Double Machine Learning in R The R package DoubleML implements the double/debiased machine learning framework of Chernozhukov, Chetverikov, Demirer, Duflo, Hansen, Newey, and Robins (2... P Bach,M Spindler,KV Chernozhukov - 《Journal of Statistical...