On the probabilistic feasibility of solutions in multi-agent optimization problems under uncertainty

We investigate the probabilistic feasibility of randomized solutions to two distinct classes of uncertain multi-agent optimization programs. We first assume that only the constraints of the program are affected by uncertainty, while the cost function is arbitrary. Leveraging recent developments on a...

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Autors principals: Pantazis, G, Fele, F, Margellos, K
Format: Journal article
Idioma:English
Publicat: Elsevier 2021