A scalable multiagent system architecture for interactive applications

Abstract

Interactive applications like crowd simulations need to properly render the virtual world while simulating the interaction of thousands of agents at the same time. The computational workload generated by these two tasks highly increases with the number of the simulated agents, requiring a scalable design of the multiagent system. In this paper, we present, in an unified manner, a distributed multiagent system architecture that can manage large crowds of autonomous agents at interactive rates while rendering multiple views of the virtual world being simulated. This architecture consists of a distributed multiagent system and a complementary distributed visualization subsystem. We also present a new scalability study of the distributed multiagent system architecture, as well as an application example. The scalability study shows that, since no system bottlenecks are present in the proposed multiagent system architecture, it can efficiently simulate population sizes of different orders of magnitude by simply adding more hardware, provided that the ratio of clients per server is appropriate for the computer platforms acting as servers. On the other hand, the application example shows that these improvements are achieved without affecting the interactivity of the simulation. Therefore, the scalability of the proposed multiagent system architecture is validated for interactive large-scale applications.