Condensed matter physics (CMP) seeks to understand the microscopic interactions of matter
at the quantum and atomistic levels, and describes how these interactions result in both …

Next generation network access technologies and Internet applications have increased the
challenge of providing satisfactory quality of experience for users with traditional congestion …

One of the field in which models of abstraction have been proposed is Artificial Intelligence
(AI). This chapter has two parts: one presents an overview of the formal models, either …

Research on interactive systems and robots, ie interactive machines that perceive, act and
communicate, has applied a multitude of different machine learning frameworks in recent …

Conversational systems and robots that use reinforcement learning for policy optimization in
large domains often face the problem of limited scalability. This problem has been …

We present an approach to the problem of learning by observation in spatially-situated
tasks, whereby an agent learns to imitate the behaviour of an observed expert, with no direct …

Many tasks in human environments require performing a sequence of navigation and
manipulation steps involving objects. In unstructured human environments, the location and …

Traditional reinforcement learning (RL) techniques often encounter limitations when solving
large or continuous stateaction spaces. Training times needed to explore the very large …

There is a rising trend in exploring the capability of inverse reinforcement learning (IRL) in
high dimensional demonstrations. Our aim is to recognise human intents from video data …

Throughout the last years, research and applications in artificial intelligence (AI) and its
subcategory machine learning (ML) have significantly increased, along with the public …