Toggle Main Menu Toggle Search

Open Access padlockePrints

Using intention recognition in a simulation platform to assess physical activity levels of an office building

Lookup NU author(s): Dr Iain SpearsORCiD


Full text for this publication is not currently held within this repository. Alternative links are provided below where available.


© Copyright 2017, International Foundation for Autonomous Agents and Multiagent Systems ( All rights reserved.Designing a building to be conducive to physical activity can significantly contribute to reducing sedentary behavior in a workplace. We aim to develop a game-based simulation platform that provides an intuitive, interactive tool to assess physical activity levels of an office building. The platform simulates workplace physical activity in a 3D virtual building. The assessors can freely manipulate spatial metrics characterizing the building's layouts and investigate their potential associations to physical activity levels. The evaluation may facilitate stakeholders to assess a building plan on public health awareness. One of the key challenges in developing such a platform lies in simulating realistic personal behavior in a complex interaction environment. In this paper, we present our initial development of the simulation platform where we focus on tackling the challenge of incorporating intention recognition in human interactions, demonstrating how this incorporation realistically affects their behaviours. Furthermore, we demonstrate the utility of collective intention recognition techniques in improving recognition reliability as well as efficiency of the simulation platform.

Publication metadata

Author(s): Zeng Y, Zhang Z, Han TA, Spears IR, Qin S

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS

Year of Conference: 2017

Pages: 1817-1819

Print publication date: 01/05/2017

Online publication date: 08/05/2017

Acceptance date: 02/04/2016

Publisher: International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)


Library holdings: Search Newcastle University Library for this item

ISBN: 9781510855076