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Probabilistic Argumentation
, 2015
"... work contained in this document has been submitted in support of an application for a degree or qualification of this or any other university or other institution of learning. All verbatim extracts have been distinguished by quotation marks, and all sources of information have been specifically ackn ..."
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acknowledged. Signed: Date: 2015 Argumentationbased reasoning is a promising approach to automated reasoning. It benefits from its ability to handle incomplete and inconsistent information. Uncertainty widely exists in knowledge bases and affects automated reasoning systems. Thus reasoning under uncertainty
Probabilistic argumentation frameworks
 In Proceedings of the first international conference on theory and applications of formal argumentation
, 2011
"... Abstract. In this paper, we extend Dung’s seminal argument framework to form a probabilistic argument framework by associating probabilities with arguments and defeats. We then compute the likelihood of some set of arguments appearing within an arbitrary argument framework induced from this probabil ..."
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Cited by 15 (1 self)
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Abstract. In this paper, we extend Dung’s seminal argument framework to form a probabilistic argument framework by associating probabilities with arguments and defeats. We then compute the likelihood of some set of arguments appearing within an arbitrary argument framework induced from
Probabilistic argumentation systems and abduction
 Annals of Mathematics and Artificial Intelligence
, 2000
"... Probabilistic argumentation systems are based on assumptionbased reasoning for obtaining arguments supporting hypotheses and on probability theory to compute probabilities of supports. Assumptionbased reasoning is closely related to hypothetical reasoning or inference through theory formation. The ..."
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Cited by 24 (10 self)
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Probabilistic argumentation systems are based on assumptionbased reasoning for obtaining arguments supporting hypotheses and on probability theory to compute probabilities of supports. Assumptionbased reasoning is closely related to hypothetical reasoning or inference through theory formation
Probabilistic argumentation systems
 Handbook of Defeasible Reasoning and Uncertainty Management Systems, Volume 5: Algorithms for Uncertainty and Defeasible Reasoning
, 2000
"... Different formalisms for solving problems of inference under uncertainty have been developed so far. The most popular numerical approach is the theory of Bayesian inference [42]. More general approaches are the DempsterShafer theory of evidence [51], and possibility theory [16], which is closely re ..."
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Cited by 63 (35 self)
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Different formalisms for solving problems of inference under uncertainty have been developed so far. The most popular numerical approach is the theory of Bayesian inference [42]. More general approaches are the DempsterShafer theory of evidence [51], and possibility theory [16], which is closely related to fuzzy systems.
Logic of Probabilistic Arguments
"... We present a logic for reasoning with probabilistic arguments to help decision making under uncertainty. The syntax of the logic is essentially modal propositional, and arguments of decision makers are expressed as sentences of the logic, with associated supports drawn from a probability dictionary. ..."
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We present a logic for reasoning with probabilistic arguments to help decision making under uncertainty. The syntax of the logic is essentially modal propositional, and arguments of decision makers are expressed as sentences of the logic, with associated supports drawn from a probability dictionary
Probabilistic argumentation and decision system
, 2003
"... The concept of probabilistic argumentation systems PAS is restricted to two types of variables: assumptions, which model the uncertain part of the knowledge, and propositions, which model the rest of the information. Instantiations of PAS have been used for dealing with problems in different context ..."
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Cited by 1 (1 self)
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The concept of probabilistic argumentation systems PAS is restricted to two types of variables: assumptions, which model the uncertain part of the knowledge, and propositions, which model the rest of the information. Instantiations of PAS have been used for dealing with problems in different
Probabilistic Argumentation with Epistemic Extensions
"... Abstract. Abstract argumentation offers an appealing way of representing and evaluating arguments and counterarguments. This approach can be enhanced by a probability assignment to each argument. There are various interpretations that can be ascribed to this assignment. In this paper, we regard the ..."
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Abstract. Abstract argumentation offers an appealing way of representing and evaluating arguments and counterarguments. This approach can be enhanced by a probability assignment to each argument. There are various interpretations that can be ascribed to this assignment. In this paper, we regard
CHRiSM and Probabilistic Argumentation Logic
"... Riveret et al. proposed a framework for probabilistic legal reasoning. Their goal is to determine the chance of winning a court case, given the chances of the judge accepting certain claims and legal rules. We tackle the same problem by defining and implementing a new formalism, called probabilis ..."
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probabilistic argumentation logic (PAL). We implement PAL in CHRiSM, and discuss how it can be seen as a probabilistic generalization of Nute’s defeasible logic. Not only does this provide an automation of the — only handperformed — computations in Riveret et al, it also provides a solution to one
Probabilistic Argumentation Systems with Decision Variables
 INFORMATICA
, 2005
"... The general concept of probabilistic argumentation systems PAS is restricted to the two types of variables: assumptions, which model the uncertain part of the knowledge, and propositions, which model the rest of the information. Here, we introduce a third kind into PAS: socalled decision variables ..."
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The general concept of probabilistic argumentation systems PAS is restricted to the two types of variables: assumptions, which model the uncertain part of the knowledge, and propositions, which model the rest of the information. Here, we introduce a third kind into PAS: socalled decision
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