Predictive & Trust-based Multi-Agent Coordination

TL;DR

This paper introduces the Anticipatory Distributed Coordination (ADC) protocol, a trust-based predictive approach enabling multi-agent systems to achieve consensus by sharing and learning from predicted future data, with proven convergence.

Contribution

The paper proposes a novel trust-based predictive consensus protocol that incorporates anticipation and learning of trust and commitment traits in multi-agent coordination.

Findings

Proven convergence using Lyapunov theory.

Demonstrated effectiveness through numerical simulations.

Enhanced coordination with trust and prediction mechanisms.

Abstract

This paper presents a trust-based predictive multi-agent consensus protocol that analyses neighbours' anticipation data and makes coordination decisions. Agents in the network share their future predicted data over a finite look-ahead horizon with their neighbours and update their predictions in a rolling-horizon fashion. The prediction data is then used by agents to learn both the trust and the commitment traits exhibited by their neighbours over time. The proposed protocol is named as the Anticipatory Distributed Coordination (ADC) protocol. Lyapunov theory-based agreement convergence between agents is provided, followed by demonstrations using numerical simulations.