A Stable Distributed Neural Controller for Physically Coupled Networked Discrete-Time System via Online Reinforcement Learning

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Reinforcement Learning in Neural Networks: A Survey

In recent years, researches on reinforcement learning (RL) have focused on bridging the gap between adaptive optimal control and bio-inspired learning techniques. Neural network reinforcement learning (NNRL) is among the most popular algorithms in the RL framework. The advantage of using neural networks enables the RL to search for optimal policies more efficiently in several real-life applicat...

متن کامل

Reinforcement Learning in Neural Networks: A Survey

In recent years, researches on reinforcement learning (RL) have focused on bridging the gap between adaptive optimal control and bio-inspired learning techniques. Neural network reinforcement learning (NNRL) is among the most popular algorithms in the RL framework. The advantage of using neural networks enables the RL to search for optimal policies more efficiently in several real-life applicat...

متن کامل

A Neural Reinforcement Learning System

In this paper we present a reinforcement learning (RL) system based on neural circuits. The neural RL system is benchmarked against a Monte Carlo (MC) RL algorithm on two tasks. The first task is the classical n-armed bandit problem and the second task is path finding in a maze. The neural RL system performs equally well or better than the MC RL algorithm. The RL system presented is very flexib...

متن کامل

Stable reinforcement learning with recurrent neural networks

In this paper, we present a technique for ensuring the stability of a large class of adaptively controlled systems. We combine IQC models of both the controlled system and the controller with a method of filtering control parameter updates to ensure stable behavior of the controlled system under adaptation of the controller. We present a specific application to a system that uses recurrent neur...

متن کامل

Reinforcement Learning via Online Linear Regression

In reinforcement learning (RL) [9], the exploration-exploitation tradeoff is the problem of deciding, given the current state and previous experience, whether to act greedily (i.e., to exploit) or non-greedily (i.e., to explore). Such a decision has to balance the conflicting objectives of maximizing reward (which is the ultimate goal of an RL agent) and acquiring knowledge about the environmen...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Complexity

سال: 2018

ISSN: 1076-2787,1099-0526

DOI: 10.1155/2018/5950678