Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
A mathematical treatment of defeasible reasoning and its implementation
Artificial Intelligence
Finding MAPs for belief networks is NP-hard
Artificial Intelligence
ACM Computing Surveys (CSUR)
Defeasible reasoning with variable degrees of justification
Artificial Intelligence
Cognitive Carpentry: A Blueprint for how to Build a Person
Cognitive Carpentry: A Blueprint for how to Build a Person
Probabilistic Networks and Expert Systems
Probabilistic Networks and Expert Systems
Credulous and Sceptical Argument Games for Preferred Semantics
JELIA '00 Proceedings of the European Workshop on Logics in Artificial Intelligence
Bayesian Artificial Intelligence
Bayesian Artificial Intelligence
Probabilistic argumentation systems a new way to combine logic with probability
Journal of Applied Logic - Special issue on combining probability and logic
A Bayesian approach to automating argumentation
NeMLaP3/CoNLL '98 Proceedings of the Joint Conferences on New Methods in Language Processing and Computational Natural Language Learning
Exploiting causal independence in Bayesian network inference
Journal of Artificial Intelligence Research
Exploratory interaction with a Bayesian argumentation system
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
MAP complexity results and approximation methods
UAI'02 Proceedings of the Eighteenth conference on Uncertainty in artificial intelligence
A bayes net approach to argumentation based negotiation
ArgMAS'04 Proceedings of the First international conference on Argumentation in Multi-Agent Systems
A study of accrual of arguments, with applications to evidential reasoning
ICAIL '05 Proceedings of the 10th international conference on Artificial intelligence and law
Subjective logic and arguing with evidence
Artificial Intelligence
An Application of Formal Argumentation: Fusing Bayes Nets in MAS
Proceedings of the 2006 conference on Computational Models of Argument: Proceedings of COMMA 2006
Argumentation based contract monitoring in uncertain domains
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Probabilistic Semantics for the Carneades Argument Model Using Bayesian Networks
Proceedings of the 2010 conference on Computational Models of Argument: Proceedings of COMMA 2010
A probabilistic approach to modelling uncertain logical arguments
International Journal of Approximate Reasoning
Probabilistic qualification of attack in abstract argumentation
International Journal of Approximate Reasoning
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This paper establishes an explicit connection between formal argumentation and Bayesian inference by introducing a notion of argument and a notion of defeat among arguments in Bayesian networks. First, the two approaches are compared and it is argued that argumentation in Bayesian belief networks is a typical multi-agent affair. Since in theories of formal argumentation the so-called admissibility semantics is an important criterion of argument validity, this paper finally proposes an algorithm to decide efficiently whether a particular node is supported by an admissible argument. The proposed algorithm is then slightly extended to an algorithm that returns the top-k of strongest admissible arguments at each node. This extension is particularly interesting from a Bayesian inference point of view, because it offers a computationally tractable alternative to the NPPP-complete decision problem k-MPE (finding the top-k most probable explanations in a Bayesian network).