activity
20172024
most citedSynergistic Team Composition: A Computational Approach to Foster Diversity in Teams

32 citations · 39 across the 5 of their papers we have counts for

collaborators

7 papers

econ.TH20245 cited

A General Approach for Computing a Consensus in Group Decision Making That Integrates Multiple Ethical Principles

Francisco Salas-Molina, Filippo Bistaffa, Juan A. Rodriguez-Aguilar

We tackle the problem of computing a consensus according to multiple ethical principles -- which can include, for example, the principle of maximum freedom associated with the Bent…

cs.AI20201 cited

A model to support collective reasoning: Formalization, analysis and computational assessment

Jordi Ganzer, Natalia Criado, Maite Lopez-Sanchez +2

Inspired by e-participation systems, in this paper we propose a new model to represent human debates and methods to obtain collective conclusions from them. This model overcomes dr…

cs.AI201932 cited

Synergistic Team Composition: A Computational Approach to Foster Diversity in Teams

Ewa Andrejczuk, Filippo Bistaffa, Christian Blum +2

Co-operative learning in heterogeneous teams refers to learning methods in which teams are organised both to accomplish academic tasks and for individuals to gain knowledge. Compet…

cs.NI2018

Decentralized dynamic task allocation for UAVs with limited communication range

Marc Pujol-Gonzalez, Jesus Cerquides, Pedro Meseguer +2

We present the Limited-range Online Routing Problem (LORP), which involves a team of Unmanned Aerial Vehicles (UAVs) with limited communication range that must autonomously coordin…

cs.MA20171 cited

Synthesising Evolutionarily Stable Normative Systems

Javier Morales, Michael Wooldridge, Juan A. Rodríguez-Aguilar +1

Within the area of multi-agent systems, normative systems are a widely used framework for the coordination of interdependent activities. A crucial problem associated with normative…

cs.MA2017

Improving Max-Sum through Decimation to Solve Loopy Distributed Constraint Optimization Problems

Jesús Cerquides, Rémi Emonet, Gauthier Picard +1

In the context of solving large distributed constraint optimization problems (DCOP), belief-propagation and approximate inference algorithms are candidates of choice. However, in g…