Personalized algorithms may quietly sabotage how people learn, nudging them into narrow tunnels of information even when they start with zero prior knowledge. In the study, participants using ...
Abstract: This paper addresses the issue of distributed predefined-time output optimization for heterogeneous multi-agent systems with equality constraints. A novel distributed algorithm is proposed ...
Abstract: This article considers distributed optimization for minimizing the average of local nonconvex cost functions, by using local information exchange over undirected communication networks. To ...
Estimation of Distribution Algorithms (EDAs) represent a class of population-based optimisation methods that replace traditional crossover and mutation operators with explicit probability modelling.
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