A Reinforcement-Learning-Based Distributed Resource Selection Algorithm for Massive IoT

Dynamic Obstacle Avoidance by Distributed Algorithm based on Reinforcement Learning (RESEARCH NOTE)

In this paper we focus on the application of reinforcement learning to obstacle avoidance in dynamic Environments in wireless sensor networks. A distributed algorithm based on reinforcement learning is developed for sensor networks to guide mobile robot through the dynamic obstacles. The sensor network models the danger of the area under coverage as obstacles, and has the property of adoption o...

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Reinforcement Learning for Algorithm Selection

Many computational problems can be solved by multiple algorithms, with different algorithms fastest for different problem sizes, input distributions, and hardware characteristics. We consider the problem of algorithm selection: dynamically choose an algorithm to attack an instance or subinstances (due to recursive calls) of a problem with the goal of minimizing the overall execution time. We fo...

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Reinforcement Learning Algorithm Selection

This paper formalises the problem of online algorithm selection in the context of Reinforcement Learning. The setup is as follows: given an episodic task and a finite number of off-policy RL algorithms, a meta-algorithm has to decide which RL algorithm is in control during the next episode so as to maximize the expected return. The article presents a novel meta-algorithm, called Epochal Stochas...

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Reinforcement Learning Algorithm Selection

This paper formalises the problem of online algorithm selection in the context of Reinforcement Learning. The setup is as follows: given an episodic task and a finite number of off-policy RL algorithms, a meta-algorithm has to decide which RL algorithm is in control during the next episode so as to maximize the expected return. The article presents a novel meta-algorithm, called Epochal Stochas...

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Reinforcement Learning Algorithm Selection

This paper formalises the problem of online algorithm selection in the context of Reinforcement Learning. The setup is as follows: given an episodic task and a finite number of off-policy RL algorithms, a meta-algorithm has to decide which RL algorithm is in control during the next episode so as to maximize the expected return. The article presents a novel meta-algorithm, called Epochal Stochas...

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A Reinforcement-Learning-Based Distributed Resource Selection Algorithm for Massive IoT

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منابع مشابه

Dynamic Obstacle Avoidance by Distributed Algorithm based on Reinforcement Learning (RESEARCH NOTE)

Reinforcement Learning for Algorithm Selection

Reinforcement Learning Algorithm Selection

Reinforcement Learning Algorithm Selection

Reinforcement Learning Algorithm Selection

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