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Corpus-Based Incremental Intention Recognition via Bayesian Network Model Construction
June 2011
CBIIRBN
We present a method for incremental intention recognition by means of incrementally constructing a Bayesian Network (BN) model as more actions are observed. It is achieved based on a knowledge base of easily maintained and constructed fragments of BNs, connecting intentions to actions. The simple structure of the fragments enables to easily and efficiently acquire the knowledge base, either from domain experts or auto- matically from a plan corpus. We show experimental results improvement for the Linux Plan Corpus. In addition, we create a new, so-called IPD Plan Corpus, for strategies in the iterated Prisoner’s Dilemma and show the experimental results for it.
In proceedings
Han The Anh, Luís Moniz Pereira
D. Pattison, D. Long, C. Geib
GAPRec 2011 - Proceedings of the 1st Workshop on Goal, Activity and Plan Recognition
Workshop of 21st International Conference on Automated Planning and Scheduling
ICAPS
http://icaps11.icaps-conference.org/
http://icaps11.icaps-conference.org/proceedings/gaprec/gaprec-pr
1-8
-
-
-
http://centria.di.fct.unl.pt/~lmp/publications/online-papers/GAPREC2011.pdf
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Han The Anh and Luís Moniz Pereira, Corpus-Based Incremental Intention Recognition via Bayesian Network Model Construction, in: D. Pattison and D. Long and C. Geib (eds), GAPRec 2011 - Proceedings of the 1st Workshop on Goal, Activity and Plan Recognition, Workshop of 21st International Conference on Automated Planning and Scheduling, ICAPS, http://icaps11.icaps-conference.org/, Vol. http://icaps11.icaps-conference.org/proceedings/gaprec/gaprec-pr, Pag. 1-8, (http://centria.di.fct.unl.pt/~lmp/publications/online-papers/GAPREC2011.pdf), June 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>Corpus-Based Incremental Intention Recognition via Bayesian Network Model Construction</b>, in: D. Pattison, D. Long and C. Geib (eds), <u>GAPRec 2011 - Proceedings of the 1st Workshop on Goal, Activity and Plan Recognition</u>, Workshop of 21st International Conference on Automated Planning and Scheduling, ICAPS, http://icaps11.icaps-conference.org/, Vol. http://icaps11.icaps-conference.org/proceedings/gaprec/gaprec-pr, Pag. 1-8, (<a href="http://centria.di.fct.unl.pt/~lmp/publications/online-papers/GAPREC2011.pdf" target="_blank">url</a>), June 2011.
@inproceedings {CBIIRBN, author = {Han The Anh and Lu\'{\i}s Moniz Pereira}, editor = {D. Pattison and D. Long and C. Geib}, title = {Corpus-Based Incremental Intention Recognition via Bayesian Network Model Construction}, booktitle = {GAPRec 2011 - Proceedings of the 1st Workshop on Goal, Activity and Plan Recognition}, series = {Workshop of 21st International Conference on Automated Planning and Scheduling}, publisher = {ICAPS}, address = {http://icaps11.icaps-conference.org/}, volume = {http://icaps11.icaps-conference.org/proceedings/gaprec/gaprec-pr}, pages = {1-8}, url = {http://centria.di.fct.unl.pt/~lmp/publications/online-papers/GAPREC2011.pdf}, abstract = {We present a method for incremental intention recognition by means of incrementally constructing a Bayesian Network (BN) model as more actions are observed. It is achieved based on a knowledge base of easily maintained and constructed fragments of BNs, connecting intentions to actions. The simple structure of the fragments enables to easily and efficiently acquire the knowledge base, either from domain experts or auto- matically from a plan corpus. We show experimental results improvement for the Linux Plan Corpus. In addition, we create a new, so-called IPD Plan Corpus, for strategies in the iterated Prisoner’s Dilemma and show the experimental results for it.}, keywords = {Corpus, Incremental Intention Recognition, Bayesian Networks}, month = {June}, year = {2011}, }
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