Reinforcement Learning (RL) has been widely explored in Traffic Signal
C...
In this paper we propose a novel bipedal locomotion controller that uses...
We study whether the learning rate α, the discount factor γ and
the rewa...
Overfitting and generalization is an important concept in Machine Learni...
Vision Transformers (VTs) are becoming a valuable alternative to
Convolu...
Reinforcement learning (RL) for traffic signal control (TSC) has shown b...
Recent progress in deep model-based reinforcement learning allows agents...
Transfer Learning (TL) is an efficient machine learning paradigm that al...
Reinforcement learning (RL) is well known for requiring large amounts of...
This paper introduces four new algorithms that can be used for tackling
...
We study the generalization properties of pruned neural networks that ar...
This paper makes one step forward towards characterizing a new family of...
We introduce a novel Deep Reinforcement Learning (DRL) algorithm called ...