Activity recognition is a key component for creating intelligent, multi-agent systems.
Intrinsically, activity recognition is a temporal classification problem. In this paper, we …

Opponent modeling is the ability to use prior knowledge and observations in order to predict
the behavior of an opponent. This survey presents a comprehensive overview of existing …

Formalizing computational models for everyday human activities remains an open
challenge. Many previous approaches towards this end assume prior knowledge about the …

One of the most common functions of smart environments is to monitor and assist older
adults with their activities of daily living. Activity recognition is a key component in this …

Models of swarming and modes of controlling them are numerous; however, to date swarm
researchers have mostly ignored a fundamental problem that impedes scalable human …

This paper addresses the problem of activity recognition for physically-embodied agent
teams. We define team activity recognition as the process of identifying team behaviors from …

This paper describes an approach to creating a simulated team of agents through
observation of another team performing a collaborative task. Simulated human teamwork …

This article addresses the problem of activity recognition for dynamic, physically embodied
agent teams. We define team activity recognition as the process of identifying team …

Automobile racing provides a unique and challenging environment for studying competitive
multi-agent behavior. In creating autonomous racing agents, one consideration is the effect …

The emerging availability of already deployed sensors that can be utilized for activity and
context recognition raised a new paradigm. This paradigm called opportunistic sensing …