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Approximation Techniques for Space-Efficient Compilation in Abductive Inference

Gregory M. Provan
2008 International Symposium on Artificial Intelligence and Mathematics  
Although generating an approximate compilation is intractable in general, we describe a preference-based PAP for which order-of-magnitude smaller compilations can be generated.  ...  We address the problem of approximately compiling propositional abduction problems (PAPs).  ...  A model of a formula f is an interpretation M that maps f to true (written M |= true). Propositional Abduction Problem We adapt the notation of to describe propositional abduction.  ... 
dblp:conf/isaim/Provan08 fatcat:tddbi5yrsbfqbg4crczuhnsap4

On Weak Constrained Argumentation Frameworks

Gianvincenzo Alfano, Sergio Greco, Francesco Parisi, Irina Trubitsyna
2021 International Conference of the Italian Association for Artificial Intelligence  
We discuss the complexity of WAFs under several well-known argumentation semantics, showing that weak constraints increase the expressive power of AFs and CAFs.  ...  Integrity constraints help to express domain knowledge in a compact and natural way, thus keeping easy the modeling task even for problems that otherwise would be hard to encode within an AF.  ...  Introduction Despite the expressive power and generality of Dung's abstract Argumentation Framework (AF) [1] , in some cases it is difficult to accurately model domain knowledge by an AF in a natural  ... 
dblp:conf/aiia/AlfanoGPT21 fatcat:3mapqfd2xzchdoqyia5sjpsbp4

Compactly representing utility functions using weighted goals and the max aggregator

Joel Uckelman, Ulle Endriss
2010 Artificial Intelligence  
Weighted propositional formulas can be used to model preferences over combinatorial domains: each formula represents a goal we would like to see satisfied, the weight of a formula represents the importance  ...  The satisfaction relation | for models and formulas is defined in the usual way for propositional logic: We give names to some types of propositional formulas: 2 The XOR we refer to here is logical XOR  ...  For a given set of propositional variables, alternatives correspond to models for propositional formulas.  ... 
doi:10.1016/j.artint.2010.07.003 fatcat:wsgi5ozkxnc6zhoesoyu6jjzxq

Reasoning, nonmonotonicity and learning in connectionist networks that capture propositional knowledge

Gadi Pinkas
1995 Artificial Intelligence  
An extended version of propositional calculus is developed and is demonstrated to be useful for nonmonotonic reasoning, dealing with conflicting beliefs and for coping with inconsistency generated by unreliable  ...  The paper presents a connectionist framework that is capable of representing and learning propositional knowledge.  ...  If I) b rp then every preferred model of $ is also a preferred model of p.  ... 
doi:10.1016/0004-3702(94)00032-v fatcat:vult74eifve7zkhm2vtifkoeey

asprin: Customizing Answer Set Preferences without a Headache

Gerhard Brewka, James Delgrande, Javier Romero, Torsten Schaub
2015 PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE  
In this paper we describe asprin, a general, flexible, and extensible framework for handling preferences among the stable models of a logic program.  ...  We also give algorithms for computing one, or all, optimal stable models of a logic program.  ...  Acknowledgement This work was partly supported by DFG research unit FOR 1513 (HYBRIS). The second author was partially supported by a Canadian NSERC Discovery Grant.  ... 
doi:10.1609/aaai.v29i1.9398 fatcat:g6elii54cravdetdkrndwddare

Expressing Preferences using Preference Set Constraint Atoms [article]

Alex Brik, Jeffrey B. Remmel
2012 arXiv   pre-print
We show that the question of whether a PSC program has a preferred stable model is CoNP-complete.  ...  expressed using preference set constraint atoms.  ...  To demonstrate the expressive power of PSC programming, we have shown that PSC programming can be used to express optimal stable models of ASO (Brewka, Niemelä, and Truszczynski 2003) , and the general  ... 
arXiv:1203.0587v1 fatcat:fmergaonynhfpd2weisfpp7whu

Measuring Knowledge for Recognition and Knowledge Entropy [article]

Fujun Hou
2018 arXiv   pre-print
Secondly, by solving the equations, formulas for measuring the levels of knowledge and the levels of ignorance are obtained in two particular cases.  ...  Finally, it is pointed out that the obtained formulas of knowledge and knowledge entropy reflect two fundamental principles: (1) The knowledge level of a group is not necessarily a simple sum of the individuals  ...  Acknowledgments The work was supported by the National Natural Science Foundation of China (No. 71571019).  ... 
arXiv:1811.06135v1 fatcat:osohz6fuvvgrhddrcadaniaxny

Representing interval orders by weighted bases: Some complexity results

Pierre Marquis, Meltem Öztürk
2009 Mathematical Social Sciences  
This paper is centered on the notion of interval order as a model for preferences.  ...  We show how interval orders can be represented by elements of those languages, called weighted bases. We identify the complexity of the main decision problems.  ...  Let us now show that a language of weighted bases for representing interval orders is strictly more expressive than the language of penalty-based representations for cardinal preferences: Proposition 5  ... 
doi:10.1016/j.mathsocsci.2008.12.011 fatcat:xcilxqw6m5eahewyb5rnij2tfe

Implementing Preferences with asprin [chapter]

Gerhard Brewka, James Delgrande, Javier Romero, Torsten Schaub
2015 Lecture Notes in Computer Science  
asprin offers a framework for expressing and evaluating combinations of quantitative and qualitative preferences among the stable models of a logic program.  ...  Moreover, we show how the computation of optimal stable models can be boosted by using declarative heuristics.  ...  A basic preference is originally expressed by a propositional formula using Boolean as well as temporal connectives.  ... 
doi:10.1007/978-3-319-23264-5_15 fatcat:yj2ruj4ezjh5ti7dvdfu2i437e

Solving conflicts in information merging by a flexible interpretation of atomic propositions

Steven Schockaert, Henri Prade
2011 Artificial Intelligence  
Although many techniques for merging conflicting propositional knowledge bases have already been proposed, most existing work is based on the idea that inconsistency results from the presence of incorrect  ...  In accordance with this view, we propose a novel approach to merging which exploits extra-logical background information about the semantic relatedness of atomic propositions.  ...  Acknowledgements We would like to thank the anonymous reviewers, whose detailed comments have greatly improved the readability of this paper.  ... 
doi:10.1016/j.artint.2011.04.001 fatcat:gjef3p7joffhjhydtvrdum2bd4

Logical Preference Representation and Combinatorial Vote

Jérôme Lang
2004 Annals of Mathematics and Artificial Intelligence  
We introduce the notion of combinatorial vote, where a group of agents (or voters) is supposed to express preferences and come to a common decision concerning a set of non-independent variables to assign  ...  of the paper entitled "From preference representation to combinatorial vote",  ...  Languages based on propositional logic are not only compact, but also particularly expressive, thanks to the expressive power of logic, and therefore they are close to intuition (ideally, a preference  ... 
doi:10.1023/b:amai.0000034522.25580.09 fatcat:k6xfk5rh2zbe5phjcrxc3eeon4

Possibilistic logic: a retrospective and prospective view

Didier Dubois, Henri Prade
2004 Fuzzy sets and systems (Print)  
Standard possibilistic logic expressions are classical logic formulas associated with weights, interpreted in the framework of possibility theory as lower bounds of necessity degrees.  ...  scales for the weights, or the management of fuzzily restricted variables.  ...  The authors are also grateful to Luis Godo for his comments, which helped improving the coverage of this review paper.  ... 
doi:10.1016/j.fss.2003.10.011 fatcat:evsmdmu67zg4thjzswir7czwjq

New Metrics between Bodies of Evidences

Pascal Djiknavorian, Dominic Grenier, Pierre Valin
2012 Journal of Emerging Technologies in Web Intelligence  
It is followed by an introduction to two new metrics we have developed: a Hamming inspired metric for evidences, and a metric based on the degree of shared uncertainty.  ...  We discuss first the extension of the Jousselme distance from the DST to the Dezert-Smarandache Theory, a generalization of the DST.  ...  ACKNOWLEDGMENT The authors wish to thank the reviewers for their comments. This work was carried out as part of Pascal jikna orian's doctoral research at Uni ersité La al.  ... 
doi:10.4304/jetwi.4.3.264-272 fatcat:qpkkihrkjrg2zc4sqcystgrd7a

Logic Based Merging

Sébastien Konieczny, Ramón Pino Pérez
2011 Journal of Philosophical Logic  
Belief merging aims at combining several pieces of information coming from different sources. In this paper we review the works on belief merging of propositional bases.  ...  There are already a lot to say in this case. 2 See for instance [5, 16, 93] for some examples of numerical data fusion, or look at the Information Fusion Journal issues.  ...  Acknowledgements The authors would like to thank the reviewers and Jérôme Lang for their remarks which have greatly contributed to improve the paper.  ... 
doi:10.1007/s10992-011-9175-5 fatcat:ntje45ahdbcpniinhemtzcdrli

Kingmakers and Leaders in Coalition Formation

D. Marc Kilgour, Steven J. Brams
2009 Social Science Research Network  
The effects of different preference assumptions-particularly, different kinds of single-peakedness-and of player weights on the number of coherent coalitions, their connectedness, and which players become  ...  We illustrate and test the model by applying it to coalition formation on the U.S.  ...  In general, the number of possible FB coalitions increases with n, the number of players, for which we gave a formula. We also gave a formula for the maximum level at which an FB coalition must form.  ... 
doi:10.2139/ssrn.1443858 fatcat:gtejs2eeobarvirwaub3sran6e
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