no code implementations • 9 Mar 2023 • Juan Marcelo Parra-Ullauri, Chen Zhen, Antonio García-Domínguez, Nelly Bencomo, Changgang Zheng, Juan Boubeta-Puig, Guadalupe Ortiz, Shufan Yang
A Reinforcement Learning (RL) system depends on a set of initial conditions (hyperparameters) that affect the system's performance.
no code implementations • 5 May 2021 • Huma Samin, Luis H. Garcia Paucar, Nelly Bencomo, Cesar M. Carranza Hurtado, Erik M. Fredericks
Decision-making for self-adaptation approaches need to address different challenges, including the quantification of the uncertainty of events that cannot be foreseen in advance and their effects, and dealing with conflicting objectives that inherently involve multi-objective decision making (e. g., avoiding costs vs. providing reliable service).
no code implementations • 22 Mar 2021 • Antonio Bucchiarone, Antonio Cicchetti, Nelly Bencomo, Enrica Loria, Annapaola Marconi
In this paper we propose our vision on how the principles at the base of the autonomous and multi-agent systems can be exploited to design multi-challenge motivational systems to engage smart communities towards common goals.