Generating Instantiated Argument Graphs from Probabilistic Information

The epistemic approach to probabilistic argumentation assigns belief to arguments. To better understand this approach, we consider structured arguments. Our approach is to start with a probability distribution, and generate an argument graph containing structured arguments with a probability assignment. We construct arguments directly from the probability distribution, rather than a knowledgebase, and then consider methods for selecting the arguments and counterarguments to present in the argument graph. This provides mechanisms for managing uncertainty in argumentation, and for argument-based explanations of probability distributions (that might come from data or from beliefs of an agent).