1 code implementation • 28 May 2024 • Camilo Chacón Sartori, Christian Blum, Filippo Bistaffa, Guillem Rodríguez Corominas
Since the rise of Large Language Models (LLMs) a couple of years ago, researchers in metaheuristics (MHs) have wondered how to use their power in a beneficial way within their algorithms.
1 code implementation • 15 Jan 2024 • 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 Benthamite doctrine and the principle of maximum fairness associated with the Rawlsian principles -- among the preferences of different individuals in the context of Group-Decision-Making.
no code implementations • 30 Apr 2022 • Adrià Fenoy, Filippo Bistaffa, Alessandro Farinelli
We consider the problem of forming collectives of agents for real-world applications aligned with Sustainable Development Goals (e. g., shared mobility, cooperative learning).
1 code implementation • 9 Aug 2021 • Filippo Bistaffa
We propose a concise function representation based on deterministic finite state automata for exact most probable explanation and constrained optimization tasks in graphical models.
no code implementations • 7 Sep 2020 • Filippo Bistaffa, Juan A. Rodríguez-Aguilar, Jesús Cerquides
Peer-to-peer ridesharing (P2P-RS) enables people to arrange one-time rides with their own private cars, without the involvement of professional drivers.
no code implementations • 26 Sep 2019 • Ewa Andrejczuk, Filippo Bistaffa, Christian Blum, Juan A. Rodríguez-Aguilar, Carles Sierra
Thus, the goal of the STCP is to partition a set of individuals into a set of synergistic teams: teams that are diverse in personality and gender and whose members cover all required competencies to complete a task.
1 code implementation • 13 Dec 2016 • Filippo Bistaffa, Alessandro Farinelli, Jesús Cerquides, Juan A. Rodríguez-Aguilar, Sarvapali D. Ramchurn
In this paper, we focus on a special case of coalition formation known as Graph-Constrained Coalition Formation (GCCF) whereby a network connecting the agents constrains the formation of coalitions.