Recommender systems (RSs) have become an inseparable part of our everyday lives. They
help us find our favorite items to purchase, our friends on social networks, and our favorite …

Abstract Safe Reinforcement Learning can be defined as the process of learning policies
that maximize the expectation of the return in problems in which it is important to ensure …

Advances in deep learning over the last decade have led to a flurry of research in the
application of deep artificial neural networks to robotic systems, with at least 30 papers …

We present a comprehensive survey of robot Learning from Demonstration (LfD), a
technique that develops policies from example state to action map**s. We introduce the …

Learning from Demonstration (LfD) explores techniques for learning a task policy from
examples provided by a human teacher. The field of LfD has grown into an extensive body …

The concept that neural information is encoded in the firing rate of neurons has been the
dominant paradigm in neurobiology for many years. This paradigm has also been adopted …

Automatic generation control (AGC) is one of the important control problems in
interconnected power system design and operation, and is becoming more significant today …

In the mammalian brain, dopamine is a critical neuromodulator whose actions underlie
learning, decision-making, and behavioral control. Degeneration of dopamine neurons …

Over a third of the anthropogenic greenhouse gas (GHG) emissions stem from cooling and
heating buildings, due to their fossil fuel based operation. Low exergy building systems are …

To make a decision, a system must assign value to each of its available choices. In the
human brain, one approach to studying valuation has used rewarding stimuli to map out …