To achieve fully autonomous driving, vehicles must be capable of continu...
Deep Reinforcement Learning (DRL) has shown remarkable success in solvin...
This paper develops a Deep Reinforcement Learning (DRL)-agent for naviga...
In the field of autonomous robots, reinforcement learning (RL) is an
inc...
The paper proposes a spatial-temporal recurrent neural network architect...
While deep reinforcement learning (RL) has been increasingly applied in
...
Value-based reinforcement-learning algorithms have shown strong performa...
In the autonomous driving field, the fusion of human knowledge into Deep...
We introduce a novel approach to dynamic obstacle avoidance based on Dee...
We propose and validate a novel car following model based on deep
reinfo...
A large number of commonly used parametric Archimedean copula (AC) famil...
Forecasting costs is now a front burner in empirical economics. We propo...
Forecasting costs is now a front burner in empirical economics. We propo...
An intensive research sprang up for stochastic methods in insurance duri...