# Aggregating Probabilistic Judgments

## TL;DR

This paper extends classical judgment aggregation methods to probabilistic opinions on related issues, proposing new aggregation functions and analyzing their properties and limitations.

## Contribution

It introduces a modified Boolean framework for probabilistic judgments and generalizes classical aggregation functions to handle probabilistic data.

## Key findings

- Proposes probabilistic aggregation functions based on classical methods.
- Identifies desirable properties and discusses impossibility results.
- Provides a theoretical foundation for aggregating probabilistic judgments.

## Abstract

In this paper we explore the application of methods for classical judgment aggregation in pooling probabilistic opinions on logically related issues. For this reason, we first modify the Boolean judgment aggregation framework in the way that allows handling probabilistic judgments and then define probabilistic aggregation functions obtained by generalization of the classical ones. In addition, we discuss essential desirable properties for the aggregation functions and explore impossibility results.