Titlebook: Parallel and Distributed Computing, Applications and Technologies; Proceedings of PDCAT Ji Su Park,Hiroyuki Takizawa,James J. Park Conferen

公共汽車(chē)

彎曲道理

-Maximum Critic Deep Deterministic Policy Gradient for Multi-agent Reinforcement Learning,hieving a local optima easily and poor convergence efficiency. To tackle the above challenges, we propose a novel algorithm, .-Maximum Critic Multi-Agent Deep Deterministic Policy Gradient algorithm (.-M2DDPG), which leverages a new critic technique called .-Maximum Critic to balance the exploitatio

laceration

Effective Density-Based Concept Drift Detection for Evolving Data Streams,r forecast, network monitoring, etc. For online data streams it is difficult to determine a proper size of the sliding window for detection of concept drift, making the existing dataset-distance based algorithms not effective in application. In this paper, we propose a novel framework of Density-bas

等級(jí)的上升

An End-to-End Multiple Hyper-parameters Prediction Method for Distributed Constraint Optimization Problem,of DCOP implement on the supercomputer, various parameters need to choose, and the complement time vary widely for different combinations of parameters. Automatically provided accurate operating parameters for DCOP can improve the operation speed and enables the rational use of computational resourc

過(guò)時(shí)

QUAIL

Wenting Dong,Jiaqi Yin,Sini Chen,Huibiao ZhuThe pharmacokinetic investigations were carried out at the 2nd University Clinic, Düsseldorf, and the results were determined in the Isotope Institute of Bayer, Wuppertal-Elberfeld, by Drs. Duhm, Maul, Medenwald, Patschke and Wegner.