This paper addresses the use of Deep Reinforcement Learning for automatic routing in Optical Transport Networks at the electrical-layer level. We propose a DRL-based solution that achieves both high performance and fast learning.Peer ReviewedPostprint (published version
Recent advances in Deep Reinforcement Learning (DRL) techniques are providing a dramatic improvement...
International audienceKnowledge-Defined networking (KDN) is a concept that relies on Software-Define...
International audienceKnowledge-Defined networking (KDN) is a concept that relies on Software-Define...
Deep reinforcement learning (DRL) has recently revolutionized the resolution of decision-making and ...
Deep Reinforcement Learning (DRL) is rising as a promising tool for solving optimization problems in...
Deep Reinforcement Learning (DRL) is rising as a promising tool for solving optimization problems in...
Deep Reinforcement Learning (DRL) is rising as a promising tool for solving optimization problems in...
Deep Reinforcement Learning (DRL) is rising as a promising tool for solving optimization problems in...
Deep Reinforcement Learning (DRL) is rising as a promising tool for solving optimization problems in...
This paper evaluates different aspects of the performance of a solution for routing and spectrum all...
Conventional schemes for service provisioning in next-generation elastic optical networks (EONs) rel...
Deep Reinforcement Learning (DRL) has shown a dramatic improvement in decision-making and automated ...
In this paper, a deep reinforcement learning routing(DRL-Routing) algorithm was proposed to solve th...
International audienceKnowledge-Defined networking (KDN) is a concept that relies on Software-Define...
Deep reinforcement learning (DRL) enables autonomic optical networking by allowing the network contr...
Recent advances in Deep Reinforcement Learning (DRL) techniques are providing a dramatic improvement...
International audienceKnowledge-Defined networking (KDN) is a concept that relies on Software-Define...
International audienceKnowledge-Defined networking (KDN) is a concept that relies on Software-Define...
Deep reinforcement learning (DRL) has recently revolutionized the resolution of decision-making and ...
Deep Reinforcement Learning (DRL) is rising as a promising tool for solving optimization problems in...
Deep Reinforcement Learning (DRL) is rising as a promising tool for solving optimization problems in...
Deep Reinforcement Learning (DRL) is rising as a promising tool for solving optimization problems in...
Deep Reinforcement Learning (DRL) is rising as a promising tool for solving optimization problems in...
Deep Reinforcement Learning (DRL) is rising as a promising tool for solving optimization problems in...
This paper evaluates different aspects of the performance of a solution for routing and spectrum all...
Conventional schemes for service provisioning in next-generation elastic optical networks (EONs) rel...
Deep Reinforcement Learning (DRL) has shown a dramatic improvement in decision-making and automated ...
In this paper, a deep reinforcement learning routing(DRL-Routing) algorithm was proposed to solve th...
International audienceKnowledge-Defined networking (KDN) is a concept that relies on Software-Define...
Deep reinforcement learning (DRL) enables autonomic optical networking by allowing the network contr...
Recent advances in Deep Reinforcement Learning (DRL) techniques are providing a dramatic improvement...
International audienceKnowledge-Defined networking (KDN) is a concept that relies on Software-Define...
International audienceKnowledge-Defined networking (KDN) is a concept that relies on Software-Define...
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