  Distributed control increases system scalability, flexibility, and
redundancy. Foundational to such decentralisation is consensus formation, by
which decision-making and coordination are achieved. However, decentralised
multi-agent systems are inherently vulnerable to disruption. To develop a
resilient consensus approach, inspiration is taken from the study of social
systems and their dynamics; specifically, the Deffuant Model. A dynamic
algorithm is presented enabling efficient consensus to be reached with an
unknown number of disruptors present within a multi-agent system. By inverting
typical social tolerance, agents filter out extremist non-standard opinions
that would drive them away from consensus. This approach allows distributed
systems to deal with unknown disruptions, without knowledge of the network
topology or the numbers and behaviours of the disruptors. A disruptor-agnostic
algorithm is particularly suitable to real-world applications where this
information is typically unknown. Faster and tighter convergence can be
achieved across a range of scenarios with the social dynamics inspired
algorithm, compared with standard Mean-Subsequence-Reduced-type methods.
