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Reinforcement learning

Known as: RL, Actor critic architecture, Reward function 
Reinforcement learning is an area of machine learning inspired by behaviorist psychology, concerned with how software agents ought to take actions in… Expand
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Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Review
2020
Review
2020
This paper introduces the Behaviour Suite for Reinforcement Learning, or bsuite for short. bsuite is a collection of carefully… Expand
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Review
2019
Review
2019
Deep learning (DL) is playing an increasingly important role in our lives. It has already made a huge impact in areas, such as… Expand
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Review
2019
Review
2019
With the breakthroughs in deep learning, the recent years have witnessed a booming of artificial intelligence (AI) applications… Expand
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Review
2019
Review
2019
Deep reinforcement learning (RL) has achieved outstanding results in recent years. This has led to a dramatic increase in the… Expand
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Review
2019
Review
2019
Multi-access edge computing (MEC), which is deployed in the proximity area of the mobile user side as a supplement to the… Expand
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Review
2019
Review
2019
This paper deals with the use of emerging deep learning techniques in future wireless communication networks. It will be shown… Expand
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Review
2019
Review
2019
Multiagent Reinforcement Learning (RL) solves complex tasks that require coordination with other agents through autonomous… Expand
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Highly Cited
2016
Highly Cited
2016
We propose a conceptually simple and lightweight framework for deep reinforcement learning that uses asynchronous gradient… Expand
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Highly Cited
2013
Highly Cited
2013
We present the first deep learning model to successfully learn control policies directly from high-dimensional sensory input… Expand
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Highly Cited
2005
Highly Cited
2005
Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning… Expand
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