RiskMan: a multi-agent system for risk management

Manolya Kavakli, Nicolas Szilas, John Porte, Iwan Kartiko

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

2 Citations (Scopus)


The purpose of this chapter is to discuss the use of multi-agent systems to develop virtual reality training systems. We first review these systems and then investigate the architectures used. We demonstrate an example of our own (RiskMan) and then discuss the advantages and drawbacks of using multi-agent agent approaches in the development of virtual reality training systems. The chapter describes the system architecture of a multi-agent system for risk management (RiskMan) to help train police officers to handle high-risk situations. RiskMan has been developed using a high-level scripting language of a game engine, Unreal Tournament 2004. The major modules are a scenario-based expert system, a narrative engine, a game engine, and a graphics engine. The system integrates a simulation agent, trainee agent, communication agent, interface agent, and scripted agents communicating using games technology.

Original languageEnglish
Title of host publicationArchitectural design of multi-agent systems
Subtitle of host publicationtechnologies and techniques
EditorsHong Lin
Place of PublicationHershey, PA; London
PublisherIGI Global
Number of pages21
ISBN (Electronic)9781599041100
ISBN (Print)9781599041087, 1599041081, 9781616927530
Publication statusPublished - 2007


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