Smart environments can already observe the actions of a human through pervasive sensors.
Based on these observations, our work aims to predict the actions a human is likely to …

Several emerging approaches to activity recognition (AR) combine symbolic representation
of user actions with probabilistic elements for reasoning under uncertainty. These …

Human activity recognition is a crucial ingredient in safe and efficient human-robot
collaboration. In this paper, we present a new model-based human activity recognition …

Human action recognition has drawn a lot of attention in the recent years due to the research
and application significance. Most existing works on action recognition focus on learning …

Goal recognisers attempt to infer an agent's intentions from a sequence of observed actions.
This is an important component of intelligent systems that aim to assist or thwart actors; …

Assistive software becomes more and more important part of our everyday life. As it is not
straightforward to create such a system, the engineering of assistive systems is a topic of …

Multiagent goal recognition is important in many simulation systems. Many of the existing
modeling methods need detailed domain knowledge of agents' cooperative behaviors and a …

Activity recognition for shepherding is a way for an artificial intelligence system to learn and
understand shepherding behaviours. The problem we describe is one of recognising …

Multiagent goal recognition is a tough yet important problem in many real time strategy
games or simulation systems. Traditional modeling methods either are in great demand of …

Goal recognition is an important component of many context-aware and smart environment
services; however, a person's goal often cannot be determined until their plan nears …