Affiliations: [a] Université Toulouse 1 Capitol – IRIT, France
| [b] Centro de Innovación Social de Alto Impacto, Instituto Tecnológico de Estudios Superiores de Occidente, Tlaquepaque, Jalisco, México | [c] División Académica de Informática y Sistemas, Universidad Juárez Autónoma de Tabasco, Cunduacán, Tabasco, México | [d]
School of Computer Science, Electrical and Electronic Engineering, and Engineering Maths, University of Bristol, Bristol, UK
Correspondence:
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Corresponding author. Oscar Chávez-Bosquez, División Académica de Informática y Sistemas, Universidad Juárez Autónoma de Tabasco, Cunduacán, Tabasco, México. E-mail: oscar.chavez@ujat.mx.
Abstract: Belief merging aims to combine pieces of information from different (and possibly conflicting) sources so as to produce a single consistent belief base which retains as much information as possible. In this paper, we describe Merginator, a logic-based tool implementing three belief merging operators presented with specific characteristics that make them interesting for comparison: ΔΣ, ΔGMax and Δps. We describe these operators while solving a set of basic examples found in the literature that we translate into natural language to provide insights for Merginator users. We also propose two more complex consensus-seeking examples: an adaptation to the role play “Lost at Sea” and the subject of administrative response to air pollution in Hong Kong. Results show that all three operators provide a consensus to the scenarios, and Δps gives the most refined consensus. This demonstrates that belief merging, is a viable technique to support consensus decision-making in many domains. Merginator is open source software available at GitHub.
