Deep reinforcement learning for autonomous driving: A survey
With the development of deep representation learning, the domain of reinforcement learning
(RL) has become a powerful learning framework now capable of learning complex policies …
(RL) has become a powerful learning framework now capable of learning complex policies …
Exploring applications of deep reinforcement learning for real-world autonomous driving systems
Deep Reinforcement Learning (DRL) has become increasingly powerful in recent years,
with notable achievements such as Deepmind's AlphaGo. It has been successfully deployed …
with notable achievements such as Deepmind's AlphaGo. It has been successfully deployed …
RL_QOptimizer: A Reinforcement Learning Based Query Optimizer
With the current availability of massive datasets and scalability requirements, different
systems are required to provide their users with the best performance possible in terms of …
systems are required to provide their users with the best performance possible in terms of …
Discrete-to-deep reinforcement learning methods
Neural networks are effective function approximators, but hard to train in the reinforcement
learning (RL) context mainly because samples are correlated. In complex problems, a …
learning (RL) context mainly because samples are correlated. In complex problems, a …