• Documents
  • Authors
  • Tables
  • Log in
  • Sign up
  • MetaCart
  • DMCA
  • Donate

CiteSeerX logo

Advanced Search Include Citations

Tools

Sorted by:
Try your query at:
Semantic Scholar Scholar Academic
Google Bing DBLP
Results 11 - 20 of 919
Next 10 →

Quantum-based Belief Merging

by Laurent Perrussel, Jerusa Marchi, Guilherme Bittencourt
"... Abstract. Belief merging aims at building a common belief set issued from mul-tiple belief sets. The quality of the resulting set is usually considered in terms of a closeness criterion between the initial belief sets and an integrity constraint with respect to the aim of the merging procedure. The ..."
Abstract - Add to MetaCart
Abstract. Belief merging aims at building a common belief set issued from mul-tiple belief sets. The quality of the resulting set is usually considered in terms of a closeness criterion between the initial belief sets and an integrity constraint with respect to the aim of the merging procedure

On Egalitarian Belief Merging

by Patricia Everaere, Pierre Marquis
"... Belief merging aims at defining the beliefs of a group of agents from the beliefs of each member of the group. It is related to more general notions of aggregation from economics (social choice theory). Two main subclasses of belief merging operators exist: majority operators which are related to ut ..."
Abstract - Add to MetaCart
Belief merging aims at defining the beliefs of a group of agents from the beliefs of each member of the group. It is related to more general notions of aggregation from economics (social choice theory). Two main subclasses of belief merging operators exist: majority operators which are related

Belief Merging with the Aim of Truthlikeness

by unknown authors
"... Abstract The merging/fusion of belief/data collections in propositional logic form is a topic that has received due attention within the domains of database and AI research. A distinction can be made between two types of scenarios to which the process of merging can be applied. In the first type, th ..."
Abstract - Add to MetaCart
Abstract The merging/fusion of belief/data collections in propositional logic form is a topic that has received due attention within the domains of database and AI research. A distinction can be made between two types of scenarios to which the process of merging can be applied. In the first type

Belief base merging as a game

by Sébastien Konieczny - Journal of Applied Non-Classical Logics , 2004
"... ABSTRACT. We propose in this paper a new family of belief merging operators, that is based on a game between sources: until a coherent set of sources is reached, at each round a contest is organized to find out the weakest sources, then those sources has to concede (weaken their point of view). This ..."
Abstract - Cited by 19 (10 self) - Add to MetaCart
ABSTRACT. We propose in this paper a new family of belief merging operators, that is based on a game between sources: until a coherent set of sources is reached, at each round a contest is organized to find out the weakest sources, then those sources has to concede (weaken their point of view

Conciliation and consensus in iterated belief merging

by Olivier Gauwin, Pierre Marquis - In Proceedings of the 8th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty , 2005
"... Abstract. Two conciliation processes for intelligent agents based on an iterated merge-then-revise change function for belief profiles are introduced and studied. The first approach is skeptical in the sense that at any revision step, each agent considers that her current beliefs are more important ..."
Abstract - Cited by 10 (3 self) - Add to MetaCart
Abstract. Two conciliation processes for intelligent agents based on an iterated merge-then-revise change function for belief profiles are introduced and studied. The first approach is skeptical in the sense that at any revision step, each agent considers that her current beliefs are more important

Belief merging and the discursive dilemma: An argument-based account to paradoxes of judgment aggregation

by Gabriella Pigozzi - Synthese , 2006
"... The aggregation of individual judgments on logically interconnected propositions into a collective decision on the same propositions is called judgment aggregation. Literature in social choice and political theory has claimed that judgment aggregation raises serious concerns. For example, consider a ..."
Abstract - Cited by 64 (11 self) - Add to MetaCart
-based procedure — are not, as I will show, satisfactory methods for group decision-making. In this paper I introduce a new aggregation procedure inspired by an operator defined in artificial intelligence in order to merge belief bases. The result is that we do not need to worry about paradoxical outcomes, since

Cautious conjunctive merging of belief functions

by Sebastien Destercke, Didier Dubois, Eric Chojnacki - Symbolic and Quantitative Approaches to Reasoning with Uncertainty, Lecture Notes in Artificial Intelligence , 2007
"... Abstract. When merging belief functions, Dempster rule of combina-tion is justied only when information sources can be considered as inde-pendent. When this is not the case, one must nd out a cautious merging rule that adds a minimal amount of information to the inputs. Such a rule is said to follow ..."
Abstract - Cited by 5 (3 self) - Add to MetaCart
Abstract. When merging belief functions, Dempster rule of combina-tion is justied only when information sources can be considered as inde-pendent. When this is not the case, one must nd out a cautious merging rule that adds a minimal amount of information to the inputs. Such a rule is said

Conciliation through Iterated Belief Merging

by Olivier Gauwin, et al. , 2007
"... Two families of conciliation processes for intelligent agents based on an iterated merge-then-revise change function for belief profiles are introduced and studied. The processes from the first family are sceptical in the sense that at any revision step, each agent considers that her current beliefs ..."
Abstract - Cited by 4 (3 self) - Add to MetaCart
Two families of conciliation processes for intelligent agents based on an iterated merge-then-revise change function for belief profiles are introduced and studied. The processes from the first family are sceptical in the sense that at any revision step, each agent considers that her current

Integrity Constraints and Truthlikeness in Belief Merging 1 Belief merging with the aim of truthlikeness

by unknown authors
"... It has been established in [1] that methods of belief merging suitable for the aim of truthlikeness do not necessarily conform to standard belief merging frameworks [2]. Following on from this work, in this note I consider how integrity constraints would work for belief merging in a truthlikeness co ..."
Abstract - Add to MetaCart
It has been established in [1] that methods of belief merging suitable for the aim of truthlikeness do not necessarily conform to standard belief merging frameworks [2]. Following on from this work, in this note I consider how integrity constraints would work for belief merging in a truthlikeness

Belief Base Rationalization for Propositional Merging

by Sébastien Konieczny, Pierre Marquis, Nicolas Schwind - PROCEEDINGS OF THE TWENTY-SECOND INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE , 2011
"... Existing belief merging operators take advantage of all the models from the bases, including those contradicting the integrity constraints. In this paper, we show that this is not suited to every merging scenario. We study the case when the bases are ”rationalized” with respect to the integrity cons ..."
Abstract - Cited by 1 (1 self) - Add to MetaCart
Existing belief merging operators take advantage of all the models from the bases, including those contradicting the integrity constraints. In this paper, we show that this is not suited to every merging scenario. We study the case when the bases are ”rationalized” with respect to the integrity
Next 10 →
Results 11 - 20 of 919
Powered by: Apache Solr
  • About CiteSeerX
  • Submit and Index Documents
  • Privacy Policy
  • Help
  • Data
  • Source
  • Contact Us

Developed at and hosted by The College of Information Sciences and Technology

© 2007-2019 The Pennsylvania State University