Semistability-Based Convergence Analysis for Paracontracting Multiagent Coordination Optimization
Qing Hui, Haopeng Zhang
TL;DR
This paper presents a convergence analysis for multiagent coordination algorithms using semistability theory, extending previous results to provide a deeper understanding of the conditions under which agents reach consensus.
Contribution
It introduces a semistability-based framework for analyzing convergence in paracontracting multiagent coordination algorithms, advancing theoretical understanding.
Findings
Established new convergence conditions for multiagent systems
Extended previous results with a semistability approach
Provided theoretical insights into agent coordination dynamics
Abstract
This sequential technical report extends some of the previous results we posted at arXiv:1306.0225.
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Taxonomy
TopicsDistributed Control Multi-Agent Systems · Mathematical and Theoretical Epidemiology and Ecology Models · Neural Networks Stability and Synchronization