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Intention Recognition with Evolution Prospection and Causal Bayesian Networks
December 2010
IREPCBN
We describe a novel approach to tackle intention recognition, by combining dynamically configurable and situation-sensitive Causal Bayes Networks plus plan generation techniques. We explore and exemplify the application, in the Elder Care context, of the ability to perform Intention Recognition and of wielding Evolution Prospection methods to help the Elder achieve its intentions. This is achieved by means of an articulate use of a Causal Bayes Network to heuristically gauge probable general intention – combined with specific generation of plans involving preferences – for checking which such in- tentions are plausibly being carried out in the specific situation at hand, and suggesting actions to the Elder. The overall approach is formulated within one coherent and general logic programming framework and implemented system. The paper recaps required background and illustrates the approach via an extended application example.
Book chapter
Luís Moniz Pereira, Han The Anh
Ana Madureira, Judite Ferreira, Zita Vale
Computational Intelligence for Engineering Systems 3: Emergent Applications
Intelligent Systems, Control and Automation: Science and Engineering Book Series
Springer
-
46
1-33
978-94-007-0092-5
-
Select updated papers from Intl. Symp. on Computational Intelligence for Engineering Systems. http://www.amazon.ca/Computational-Intelligence-Engineering-Systems-Applications/dp/940070092X
http://centria.di.fct.unl.pt/~lmp/publications/online-papers/IR-EPA-CBNs-book.pdf
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Luís Moniz Pereira and Han The Anh, Intention Recognition with Evolution Prospection and Causal Bayesian Networks, in: Ana Madureira and Judite Ferreira and Zita Vale (eds), Computational Intelligence for Engineering Systems 3: Emergent Applications, Intelligent Systems, Control and Automation: Science and Engineering Book Series, Springer, Vol. 46, ISBN 978-94-007-0092-5, Pag. 1-33, (http://centria.di.fct.unl.pt/~lmp/publications/online-papers/IR-EPA-CBNs-book.pdf), Select updated papers from Intl. Symp. on Computational Intelligence for Engineering Systems. http://www.amazon.ca/Computational-Intelligence-Engineering-Systems-Applications/dp/940070092X, December 2010.
<a href="/people/members/view.php?code=6175f826202ff877fba2ad77784cb9cb" class="author">Luís Moniz Pereira</a> and <a href="/people/members/view.php?code=cdc7090d1f84f56c0671baa36e87bd77" class="author">Han The Anh</a>, <b>Intention Recognition with Evolution Prospection and Causal Bayesian Networks</b>, in: Ana Madureira, Judite Ferreira and Zita Vale (eds), <u>Computational Intelligence for Engineering Systems 3: Emergent Applications</u>, Intelligent Systems, Control and Automation: Science and Engineering Book Series, <a href="http://www.springer.com" title="Link to external entity..." target="_blank" class="publisher">Springer</a>, Vol. 46, ISBN 978-94-007-0092-5, Pag. 1-33, (<a href="http://centria.di.fct.unl.pt/~lmp/publications/online-papers/IR-EPA-CBNs-book.pdf" target="_blank">url</a>), <i>Select updated papers from Intl. Symp. on Computational Intelligence for Engineering Systems. http://www.amazon.ca/Computational-Intelligence-Engineering-Systems-Applications/dp/940070092X</i>, December 2010.
@incollection {IREPCBN, author = {Lu\'{\i}s Moniz Pereira and Han The Anh}, editor = {Ana Madureira and Judite Ferreira and Zita Vale}, title = {Intention Recognition with Evolution Prospection and Causal Bayesian Networks}, booktitle = {Computational Intelligence for Engineering Systems 3: Emergent Applications}, series = {Intelligent Systems, Control and Automation: Science and Engineering Book Series}, publisher = {Springer}, volume = {46}, pages = {1-33}, isbn = {978-94-007-0092-5}, note = {Select updated papers from Intl. Symp. on Computational Intelligence for Engineering Systems. http://www.amazon.ca/Computational-Intelligence-Engineering-Systems-Applications/dp/940070092X}, url = {http://centria.di.fct.unl.pt/~lmp/publications/online-papers/IR-EPA-CBNs-book.pdf}, abstract = {We describe a novel approach to tackle intention recognition, by combining dynamically configurable and situation-sensitive Causal Bayes Networks plus plan generation techniques. We explore and exemplify the application, in the Elder Care context, of the ability to perform Intention Recognition and of wielding Evolution Prospection methods to help the Elder achieve its intentions. This is achieved by means of an articulate use of a Causal Bayes Network to heuristically gauge probable general intention – combined with specific generation of plans involving preferences – for checking which such in- tentions are plausibly being carried out in the specific situation at hand, and suggesting actions to the Elder. The overall approach is formulated within one coherent and general logic programming framework and implemented system. The paper recaps required background and illustrates the approach via an extended application example.}, keywords = {Intention recognition, Elder Care, Causal Bayes Networks, Plan generation, Evolution Prospection, Preferences, Logic Programming}, month = {December}, year = {2010}, }
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