Asymptotic Consensus Without Self-Confidence
For distributed systems and multi-agent networks, it relaxes the common self-confidence assumption, enabling consensus in more realistic scenarios.
The paper shows that asymptotic consensus can be achieved without agents having self-confidence, provided the network contains aperiodic cores, which act as distributed memory. This extends consensus results to systems with message delays and memory loss.
This paper studies asymptotic consensus in systems in which agents do not necessarily have self-confidence, i.e., may disregard their own value during execution of the update rule. We show that the prevalent hypothesis of self-confidence in many convergence results can be replaced by the existence of aperiodic cores. These are stable aperiodic subgraphs, which allow to virtually store information about an agent's value distributedly in the network. Our results are applicable to systems with message delays and memory loss.