Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Handbook of logic in artificial intelligence and logic programming (vol. 3)
A logic-based theory of deductive arguments
Artificial Intelligence
A Maximum Entropy Approach to Nonmonotonic Reasoning
IEEE Transactions on Pattern Analysis and Machine Intelligence
SCC-recursiveness: a general schema for argumentation semantics
Artificial Intelligence
On the evaluation of argumentation formalisms
Artificial Intelligence
On principle-based evaluation of extension-based argumentation semantics
Artificial Intelligence
Proceedings of the 2006 conference on Computational Models of Argument: Proceedings of COMMA 2006
Proceedings of the 2010 conference on Computational Models of Argument: Proceedings of COMMA 2010
Some reflections on two current trends in formal argumentation
Logic Programs, Norms and Action
ONTOarg: A decision support framework for ontology integration based on argumentation
Expert Systems with Applications: An International Journal
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The past ten years have shown a great variety of approaches for formal argumentation. An interesting question is to which extent these various formalisms correspond to the different application domains. That is, does the appropriate argumentation formalism depend on the particular domain of application, or does “one size fits all”. In this paper, we study this question from the perspective of one relatively simple design consideration: should or should there not be contrapostion of (or modus tollens) on defeasible rules. We aim to show that the answer depends on whether one is considering epistemical or constitutive reasoning, and that hence different domains require fundamentally different forms of defeasible reasoning.