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Context-dependent Incremental Intention Recognition through Bayesian Network Model Construction
July 2011
CIIRBN
We present a method for context-dependent and incremental intention recognition by means of incrementally constructing a Bayesian Network (BN) model as more actions are observed. It is achieved with the support of a knowledge base of readily maintained and constructed fragments of BNs. The simple structure of the fragments enables to easily and efficiently acquire the knowledge base, either from domain experts or automatically from a plan corpus. We exhibit experimental results improvement for the Linux Plan corpus. For additional experimentation, new plan corpora for the iterated Prisoner’s Dilemma are created. We show that taking into account con- textual information considerably increases intention recognition performance.
In proceedings
Han The Anh, Luís Moniz Pereira
Procs. 8th UAI Workshop on Bayesian Modeling Applications (BMAW 2011)
Workshop of Conf. on Uncertainty in Artificial Intelligence (UAI-2011)
CEUR Workshop Proceedings
http://ceur-ws.org/Vol-818/
818
50-58
-
1613-0073
urn:nbn:de:0074-818-8 http://centria.di.fct.unl.pt/~lmp/publications/online-papers/UAI_workshop.pdf
http://ceur-ws.org/Vol-818/paper7.pdf
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Han The Anh and Luís Moniz Pereira, Context-dependent Incremental Intention Recognition through Bayesian Network Model Construction, , Procs. 8th UAI Workshop on Bayesian Modeling Applications (BMAW 2011), Workshop of Conf. on Uncertainty in Artificial Intelligence (UAI-2011), CEUR Workshop Proceedings, http://ceur-ws.org/Vol-818/, Vol. 818, ISSN 1613-0073, Pag. 50-58, (http://ceur-ws.org/Vol-818/paper7.pdf), urn:nbn:de:0074-818-8 http://centria.di.fct.unl.pt/~lmp/publications/online-papers/UAI_workshop.pdf, July 2011.
<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>Context-dependent Incremental Intention Recognition through Bayesian Network Model Construction</b>, <u>Procs. 8th UAI Workshop on Bayesian Modeling Applications (BMAW 2011)</u>, Workshop of Conf. on Uncertainty in Artificial Intelligence (UAI-2011), CEUR Workshop Proceedings, http://ceur-ws.org/Vol-818/, Vol. 818, ISSN 1613-0073, Pag. 50-58, (<a href="http://ceur-ws.org/Vol-818/paper7.pdf" target="_blank">url</a>), <i>urn:nbn:de:0074-818-8 http://centria.di.fct.unl.pt/~lmp/publications/online-papers/UAI_workshop.pdf</i>, July 2011.
@inproceedings {CIIRBN, author = {Han The Anh and Lu\'{\i}s Moniz Pereira}, title = {Context-dependent Incremental Intention Recognition through Bayesian Network Model Construction}, booktitle = {Procs. 8th UAI Workshop on Bayesian Modeling Applications (BMAW 2011)}, series = {Workshop of Conf. on Uncertainty in Artificial Intelligence (UAI-2011)}, publisher = {CEUR Workshop Proceedings}, address = {http://ceur-ws.org/Vol-818/}, volume = {818}, pages = {50-58}, issn = {1613-0073}, note = {urn:nbn:de:0074-818-8 http://centria.di.fct.unl.pt/~lmp/publications/online-papers/UAI_workshop.pdf}, url = {http://ceur-ws.org/Vol-818/paper7.pdf}, abstract = {We present a method for context-dependent and incremental intention recognition by means of incrementally constructing a Bayesian Network (BN) model as more actions are observed. It is achieved with the support of a knowledge base of readily maintained and constructed fragments of BNs. The simple structure of the fragments enables to easily and efficiently acquire the knowledge base, either from domain experts or automatically from a plan corpus. We exhibit experimental results improvement for the Linux Plan corpus. For additional experimentation, new plan corpora for the iterated Prisoner’s Dilemma are created. We show that taking into account con- textual information considerably increases intention recognition performance.}, keywords = {Intention Recognition, Bayesian Networks}, month = {July}, year = {2011}, }
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