Explaining aggregate behaviour in cognitive agent simulations using explanation

Abstract

We consider the problem of obtaining useful (and actionable) insight into the behaviour of agent-based simulation (using cognitive agents). When such simulations are being developed and refined, it can be useful to gain understanding of the simulation’s behaviour. In particular, such understanding often needs to be specific to a given scenario (not just high-level generic information about the simulation dynamics), and about the aggregate behaviour of multiple agents. We describe a method for taking explanations of behaviour produced by individual agents, and aggregating them to obtain useful information about the aggregate behaviour of multiple agents. The method, which has been implemented, is illustrated in the context of a traffic simulation.