Agent-based simulation of dynamic online auctions
Proceedings of the 32nd conference on Winter simulation
Efficient agent-based simulation framework for multi-node supercomputers
Proceedings of the 38th conference on Winter simulation
Agent server technology for managing millions of agents
MMAS'04 Proceedings of the First international conference on Massively Multi-Agent Systems
Multi-model based simulation platform for urban traffic simulation
PRIMA'10 Proceedings of the 13th international conference on Principles and Practice of Multi-Agent Systems
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Agent based simulation (ABS) is efficient for the simulation of objects whose mathematical modeling is not easy. There are many studies on ABS and several frameworks for ABS have already been published. However, there are few frameworks that can enable agent-based simulation using large numbers of agents. We have been developing a Java-based platform for Massive Agent-Based Simulation (MABS) called "Zillions of Agents-based Simulation Environment" or ZASE. The purpose of ZASE is to develop MABS applications on multiple general computers such as PCs or workstations where they are connected with a high performance but generally available network such as gigabit Ethernet. ZASE is designed to host over millions of agents. In this paper, we introduce ZASE and explain the fundamental capabilities for MABS provided by ZASE. We evaluated ZASE for the agent-based auction simulation where the number of agents varied from ten to a million. The results indicate that the number of agents affects the final bid prices and their distributions. Performance measurement results on both an SMP computer environment and a multiple-computer environment are shown. The results in the both cases were about 3.5 millions of times of that agents handle messages in a second. The scalability ratio on the SMP computer and the multiple-computers environment were 78% and 85% respectively. Those scalability ratios are such good values for the simulations.