Evolving goal-driven multi-agent communication: what, when, and to whom

Abstract

This paper presents an evolutionary approach that, given a performance goal, produces a communication strategy that can improve a multi-agent system’s performance with respect to the desired goal. The evolved strategy determines what, when, and to whom agents communicate. The proposed approach further enables tuning the trade-off between the performance goal and communication cost, to produce a strategy that achieves a good balance between the two objectives, according the system’s designer needs. Experiments are designed to evaluate the approach using the Wumpus World application domain, with variations of three factors: fitness parameters (including objectives’ weights and action and communication costs), fitness goal, and simulation environment. Results show that the system’s performance can be highly tuned by controlling communication, and that the presented approach has significant utilization in improving the performance with respect to the goal.