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Proactive Intention Recognition for Home Ambient Intelligence
July 2010
PIRHAI
We explore a coherent combination of two jointly implemented logic programming based systems, namely Evolution Prospection and Intention Recognition, to address issues pertinent for Ambient Intelligence (AmI) in the home environment context. The Evolution Prospection system designs and implements several kinds of well-studied preferences and useful environment-triggering constructs for decision making. These enable a convenient declarative encoding of users’ preferences and needs, and reactive constructs like goal triggering rules. The other system performs intention recognition by means of Causal Bayes Nets and a planner. This approach to intention recognition is appropriate to tackle several AmI issues, such as security and emergency. We also present a novel method for collective intention recognition to allow tackling the case where multiple users are of concern. We exemplify with examples in the elder care domain as it is one typical concern in the home environment context.
In proceedings
Han The Anh, Luís Moniz Pereira
R. López-Cózar et al.
Ambient Intelligence and Smart Environments
6th Intl. Conf. Intelligent Environments (IE10)
IOS Press
http://www.iospress.nl/
8
91-100
978-1-60750-638-6
-
5th Workshop on Artificial Intelligence Techniques for Ambient Intelligence (AITAmI'10) at 6th Intl. Conf. Intelligent Environments (IE10)
http://centria.di.fct.unl.pt/~lmp/publications/online-papers/AITAmI10.pdf
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Han The Anh and Luís Moniz Pereira, Proactive Intention Recognition for Home Ambient Intelligence, in: R. López-Cózar et al. (eds), Ambient Intelligence and Smart Environments, 6th Intl. Conf. Intelligent Environments (IE10), IOS Press, http://www.iospress.nl/, Vol. 8, ISBN 978-1-60750-638-6, Pag. 91-100, (http://centria.di.fct.unl.pt/~lmp/publications/online-papers/AITAmI10.pdf), 5th Workshop on Artificial Intelligence Techniques for Ambient Intelligence (AITAmI'10) at 6th Intl. Conf. Intelligent Environments (IE10), July 2010.
<a href="/people/members/view.php?code=cdc7090d1f84f56c0671baa36e87bd77" class="author">Han The Anh</a> and <a href="/people/members/view.php?code=6175f826202ff877fba2ad77784cb9cb" class="author">Luís Moniz Pereira</a>, <b>Proactive Intention Recognition for Home Ambient Intelligence</b>, in: R. López-Cózar et al. (eds), <u>Ambient Intelligence and Smart Environments</u>, 6th Intl. Conf. Intelligent Environments (IE10), <a href="http://www.iospress.nl/" title="Link to external entity..." target="_blank" class="publisher">IOS Press</a>, http://www.iospress.nl/, Vol. 8, ISBN 978-1-60750-638-6, Pag. 91-100, (<a href="http://centria.di.fct.unl.pt/~lmp/publications/online-papers/AITAmI10.pdf" target="_blank">url</a>), <i>5th Workshop on Artificial Intelligence Techniques for Ambient Intelligence (AITAmI'10) at 6th Intl. Conf. Intelligent Environments (IE10)</i>, July 2010.
@inproceedings {PIRHAI, author = {Han The Anh and Lu\'{\i}s Moniz Pereira}, editor = {R. L{\'o}pez-C{\'o}zar et al.}, title = {Proactive Intention Recognition for Home Ambient Intelligence}, booktitle = {Ambient Intelligence and Smart Environments}, series = {6th Intl. Conf. Intelligent Environments (IE10)}, publisher = {IOS Press}, address = {http://www.iospress.nl/}, volume = {8}, pages = {91-100}, isbn = {978-1-60750-638-6}, note = {5th Workshop on Artificial Intelligence Techniques for Ambient Intelligence (AITAmI'10) at 6th Intl. Conf. Intelligent Environments (IE10)}, url = {http://centria.di.fct.unl.pt/~lmp/publications/online-papers/AITAmI10.pdf}, abstract = {We explore a coherent combination of two jointly implemented logic programming based systems, namely Evolution Prospection and Intention Recognition, to address issues pertinent for Ambient Intelligence (AmI) in the home environment context. The Evolution Prospection system designs and implements several kinds of well-studied preferences and useful environment-triggering constructs for decision making. These enable a convenient declarative encoding of users’ preferences and needs, and reactive constructs like goal triggering rules. The other system performs intention recognition by means of Causal Bayes Nets and a planner. This approach to intention recognition is appropriate to tackle several AmI issues, such as security and emergency. We also present a novel method for collective intention recognition to allow tackling the case where multiple users are of concern. We exemplify with examples in the elder care domain as it is one typical concern in the home environment context.}, keywords = {Evolution Prospection, Preferences, Intention Recognition, Ambient Intelligence, Logic Programming}, month = {July}, year = {2010}, }
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