DOT and DOP: Linearly Convergent Algorithms for Finding Fixed Points of Multi-Agent Operators

نویسندگان

چکیده

This paper investigates the distributed fixed-point finding problem for a global operator over directed and unbalanced multi-agent network, where is quasi-nonexpansive only partially accessible to each individual agent. Two cases are addressed, that is, sum separable block separable. For this first case, of local operators, which assumed be Lipschitz, privately known To deal with scenario, (or decentralized) algorithm, called Distributed quasi-averaged Operator Tracking algorithm (DOT), proposed analyzed, it shown can converge fixed point at linear rate under regularity condition, strictly weaker than strong convexity assumption on cost functions in existing convex optimization literature. second composed group mappings Lipschitz accessed by In setup, Playing (DOP), developed linearly convergent condition. The above studied problems provide unified framework many interesting problems. As examples, DOT DOP exploited cope multi-player games partial-decision information. Finally, numerical examples presented corroborate theoretical results.

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ژورنال

عنوان ژورنال: IEEE Transactions on Automatic Control

سال: 2023

ISSN: ['0018-9286', '1558-2523', '2334-3303']

DOI: https://doi.org/10.1109/tac.2023.3312137