A general approach for consensus using optimistic planning
Lucian Buşoniu, Irinel‐Constantin Morărescu · 2013
An important challenge in multiagent systems is consensus, in which the agents are required to synchronize certain controlled variables of interest, often using only an incomplete and time-varying communication graph. We propose a consensus approach based on optimistic planning (OP), a predictive control algorithm that finds near-optimal control actions for general dynamics and reward functions (costs). At every step, each agent uses OP to solve a local control problem with rewards that express the consensus objectives. Neighboring agents coordinate by exchanging their predicted behaviors in a predefined order. Due to its generality, OP consensus can adapt to any agent dynamics and, by changing the reward function, to a variety of consensus objectives. While theoretical analysis is still open, OP consensus is demonstrated in experiments for two problems. The first problem is velocity consensus (flocking) with a time-varying communication graph, where OP preserves connectivity better than a classical algorithm. The second problem is the leaderless and leader-based consensus of robotic arms, where OP easily deals with the nonlinear dynamics.