Deep reinforcement learning: An overview

Y Li - arxiv preprint arxiv:1701.07274, 2017‏ - arxiv.org
We give an overview of recent exciting achievements of deep reinforcement learning (RL).
We discuss six core elements, six important mechanisms, and twelve applications. We start …

[HTML][HTML] A survey of deep reinforcement learning application in 5G and beyond network slicing and virtualization

C Ssengonzi, OP Kogeda, TO Olwal - Array, 2022‏ - Elsevier
Abstract The 5th Generation (5G) and beyond networks are expected to offer huge
throughputs, connect large number of devices, support low latency and large numbers of …

[کتاب][B] Synthetic data for deep learning

SI Nikolenko - 2021‏ - Springer
You are holding in your hands… oh, come on, who holds books like this in their hands
anymore? Anyway, you are reading this, and it means that I have managed to release one of …

An introduction to deep reinforcement learning

V François-Lavet, P Henderson, R Islam… - … and Trends® in …, 2018‏ - nowpublishers.com
Deep reinforcement learning is the combination of reinforcement learning (RL) and deep
learning. This field of research has been able to solve a wide range of complex …

[کتاب][B] Neural networks and deep learning

CC Aggarwal - 2018‏ - Springer
“Any AI smart enough to pass a Turing test is smart enough to know to fail it.”–*** Ian
McDonald Neural networks were developed to simulate the human nervous system for …

Ray: A distributed framework for emerging {AI} applications

P Moritz, R Nishihara, S Wang, A Tumanov… - … USENIX symposium on …, 2018‏ - usenix.org
The next generation of AI applications will continuously interact with the environment and
learn from these interactions. These applications impose new and demanding systems …

Starcraft ii: A new challenge for reinforcement learning

O Vinyals, T Ewalds, S Bartunov, P Georgiev… - arxiv preprint arxiv …, 2017‏ - arxiv.org
This paper introduces SC2LE (StarCraft II Learning Environment), a reinforcement learning
environment based on the StarCraft II game. This domain poses a new grand challenge for …

Adaptive power system emergency control using deep reinforcement learning

Q Huang, R Huang, W Hao, J Tan… - IEEE Transactions on …, 2019‏ - ieeexplore.ieee.org
Power system emergency control is generally regarded as the last safety net for grid security
and resiliency. Existing emergency control schemes are usually designed offline based on …

A gentle introduction to reinforcement learning and its application in different fields

M Naeem, STH Rizvi, A Coronato - IEEE access, 2020‏ - ieeexplore.ieee.org
Due to the recent progress in Deep Neural Networks, Reinforcement Learning (RL) has
become one of the most important and useful technology. It is a learning method where a …

Deep reinforcement learning

SE Li - Reinforcement learning for sequential decision and …, 2023‏ - Springer
Similar to humans, RL agents use interactive learning to successfully obtain satisfactory
decision strategies. However, in many cases, it is desirable to learn directly from …