Open Source Voting Software

This collection of Python3 modules provides a large range of implemented decision aiding algorithms useful in the field of outranking digraphs based Multiple Criteria Decision Aid (MCDA), especially best choice, linear ranking and absolute or relative rating algorithms with multiple incommensurable criteria. Technical documentation and tutorials are available under the following link: https://digraph3.readthedocs.io/en/latest/ The tutorials introduce the main objects like digraphs, outranking digraphs and performance tableaux. There is also a tutorial provided on undirected graphs. Some tutorials are problem oriented and show how to compute the winner of an election, how to build a best choice recommendation, or how to linearly rank or rate with multiple incommensurable performance criteria. Other tutorials concern more specifically operational aspects of computing maximal independent sets (MISs) and kernels in graphs and digraphs.

Belief merging aims at combining several pieces of (possibly inconsistent) information coming from different sources. The goal is to produce a single consistent set of information, trying to keep the most of the information of the sources. A belief merging operator is the responsible for making the belief merging. With this tool you can compare the ΔΣ, ΔGMax and the Δps (PS-Merge) operators.

Belief revision is a central topic in knowledge representation and reasoning. It consists in incorporating a new belief, changing as few as possible of the original beliefs while preserving consistency. Revision always considers new evidence as a better belief. Such new evidence is usually represented in the form of a propositional formula which must be preserved after the revision. Here, the Δps (PS-Merge) belief merging operator is extended in order to consider constraints, and this extension is used as a strategy for belief revision. The new evidence is treated as a constraint so the extended merging operator can obtain the revised belief base.

Accompanying software for the paper "Optimal Decision Rules for the Discursive Dilemma", by A. Alabert, M. Farré and R. Montes (https://arxiv.org/abs/2210.13100). Computes a ranking of the best decision rules according to a quantitative criterion based on the minimisation of the combined probabilities of false positives and false negatives

A rich client to analyse data from a liquid-feedback (http://liquidfeedback.org/) instance, for now it's a 3d graph explorer to inspect the delegations. It's an application based on the eclipse platform (indigo). To be precise its a directed weighted multi graph browser in 3d. Find out more in the wiki https://sourceforge.net/p/lqfbanalyser/wiki/Home/ . Generated reports https://sourceforge.net/p/lqfbanalyser/wiki/generated%20lqfb%20reports/ .

Uses the USGS Watershed Boundary Dataset and the 2010 US Census data to create representational voting districts with equivalent population.