This paper establishes existence, uniqueness, and a finite-particle mean-field error rate of order N^{-γ} for a multi-species consensus-based algorithm for multiplayer Nash games.
On the mean-field limit for the consensus-based optimization
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
abstract
This paper is concerned with the large particle limit for the consensus-based optimization (CBO), which was postulated in the pioneering works [6,28]. In order to solve this open problem, we adapt a compactness argument by first proving the tightness of the empirical measures $\{\mu^N\}_{N\geq 2}$ associated to the particle system and then verifying that the limit measure $\mu$ is the unique weak solution to the mean-field CBO equation. Such results are extended to the model of particle swarm optimization (PSO).
citation-role summary
background 1
citation-polarity summary
fields
math.OC 1years
2025 1verdicts
CONDITIONAL 1roles
background 1polarities
background 1representative citing papers
citing papers explorer
-
Well-posedness and mean-field limit estimate of a consensus-based algorithm for multiplayer games
This paper establishes existence, uniqueness, and a finite-particle mean-field error rate of order N^{-γ} for a multi-species consensus-based algorithm for multiplayer Nash games.