Aggregation of probabilisitic logically related judgments
Information aggregation is at the core of many problems in computer science. Judgement aggregation models multi-agent decision making by aggregating individual opinions from various sources. It does however assume that the sources are certain in their opinions and also subject to the same logical constraints. We relax both of these assumptions and build a more general framework with uncertain information sources that we model in probabilistic logic. We also propose aggregation functions for this new framework.