Partial Preferences and Ambiguity Resolution in Contextual Defeasible Logic

Antonis Bikakis; Grigoris Antoniou

doi:10.1007/978-3-642-20895-9_18

Partial Preferences and Ambiguity Resolution in Contextual Defeasible Logic

Antonis Bikakis, Grigoris Antoniou

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

6 Citations (Scopus)

Abstract

Domains, such as Ambient Intelligence and Social Networks, are characterized by some common features including distribution of the available knowledge, entities with different backgrounds, viewpoints and operational environments, and imperfect knowledge. Multi-Context Systems (MCS) has been proposed as a natural representation model for such environments, while recent studies have proposed adding non-monotonic features to MCS to address the issues of incomplete, uncertain and ambiguous information. In previous works, we introduced a non-monotonic extension to MCS and an argument-based reasoning model that handle imperfect context information based on defeasible argumentation. Here we propose alternative variants that integrate features such as partial preferences, ambiguity propagating and team defeat, and study the relations between the different variants in terms of conclusions being drawn in each case.

Original language	English
Title of host publication	Logic Programming and Nonmonotonic Reasoning
Subtitle of host publication	11th International Conference, LPNMR 2011, Proceedings
Editors	James P. Delgrande, Wolfgang Faber
Publisher	Springer-Verlag Berlin Heidelberg
Pages	193-198
Number of pages	6
Volume	6645 LNCS/LNAI
ISBN (Electronic)	9783642208959
ISBN (Print)	9783642208942
DOIs	https://doi.org/10.1007/978-3-642-20895-9_18
Publication status	Published - 2 May 2011
Externally published	Yes
Event	11th International Conference on Logic Programming and Nonmonotonic Reasoning - Vancouver, Canada Duration: 16 May 2011 → 19 May 2011 Conference number: 11

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Publisher	Springer-Verlag Berlin Heidelberg
Volume	6645 LNCS/LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	11th International Conference on Logic Programming and Nonmonotonic Reasoning
Abbreviated title	LPNMR 2011
Country/Territory	Canada
City	Vancouver
Period	16/05/11 → 19/05/11

Access to Document

10.1007/978-3-642-20895-9_18Licence: Unspecified

Cite this

Bikakis, A., & Antoniou, G. (2011). Partial Preferences and Ambiguity Resolution in Contextual Defeasible Logic. In J. P. Delgrande, & W. Faber (Eds.), Logic Programming and Nonmonotonic Reasoning : 11th International Conference, LPNMR 2011, Proceedings (Vol. 6645 LNCS/LNAI, pp. 193-198). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6645 LNCS/LNAI). Springer-Verlag Berlin Heidelberg. https://doi.org/10.1007/978-3-642-20895-9_18

Bikakis, Antonis ; Antoniou, Grigoris. / Partial Preferences and Ambiguity Resolution in Contextual Defeasible Logic. Logic Programming and Nonmonotonic Reasoning : 11th International Conference, LPNMR 2011, Proceedings. editor / James P. Delgrande ; Wolfgang Faber. Vol. 6645 LNCS/LNAI Springer-Verlag Berlin Heidelberg, 2011. pp. 193-198 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "Domains, such as Ambient Intelligence and Social Networks, are characterized by some common features including distribution of the available knowledge, entities with different backgrounds, viewpoints and operational environments, and imperfect knowledge. Multi-Context Systems (MCS) has been proposed as a natural representation model for such environments, while recent studies have proposed adding non-monotonic features to MCS to address the issues of incomplete, uncertain and ambiguous information. In previous works, we introduced a non-monotonic extension to MCS and an argument-based reasoning model that handle imperfect context information based on defeasible argumentation. Here we propose alternative variants that integrate features such as partial preferences, ambiguity propagating and team defeat, and study the relations between the different variants in terms of conclusions being drawn in each case.",

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Bikakis, A & Antoniou, G 2011, Partial Preferences and Ambiguity Resolution in Contextual Defeasible Logic. in JP Delgrande & W Faber (eds), Logic Programming and Nonmonotonic Reasoning : 11th International Conference, LPNMR 2011, Proceedings. vol. 6645 LNCS/LNAI, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6645 LNCS/LNAI, Springer-Verlag Berlin Heidelberg, pp. 193-198, 11th International Conference on Logic Programming and Nonmonotonic Reasoning, Vancouver, British Columbia, Canada, 16/05/11. https://doi.org/10.1007/978-3-642-20895-9_18

Partial Preferences and Ambiguity Resolution in Contextual Defeasible Logic. / Bikakis, Antonis; Antoniou, Grigoris.

Logic Programming and Nonmonotonic Reasoning : 11th International Conference, LPNMR 2011, Proceedings. ed. / James P. Delgrande; Wolfgang Faber. Vol. 6645 LNCS/LNAI Springer-Verlag Berlin Heidelberg, 2011. p. 193-198 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6645 LNCS/LNAI).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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N2 - Domains, such as Ambient Intelligence and Social Networks, are characterized by some common features including distribution of the available knowledge, entities with different backgrounds, viewpoints and operational environments, and imperfect knowledge. Multi-Context Systems (MCS) has been proposed as a natural representation model for such environments, while recent studies have proposed adding non-monotonic features to MCS to address the issues of incomplete, uncertain and ambiguous information. In previous works, we introduced a non-monotonic extension to MCS and an argument-based reasoning model that handle imperfect context information based on defeasible argumentation. Here we propose alternative variants that integrate features such as partial preferences, ambiguity propagating and team defeat, and study the relations between the different variants in terms of conclusions being drawn in each case.

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Bikakis A, Antoniou G. Partial Preferences and Ambiguity Resolution in Contextual Defeasible Logic. In Delgrande JP, Faber W, editors, Logic Programming and Nonmonotonic Reasoning : 11th International Conference, LPNMR 2011, Proceedings. Vol. 6645 LNCS/LNAI. Springer-Verlag Berlin Heidelberg. 2011. p. 193-198. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-20895-9_18

Partial Preferences and Ambiguity Resolution in Contextual Defeasible Logic

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