A Multi-agent based Approach to simulate uncertainty of a crowd In panic with sharable ontologies

Abstract

Crowd simulation is listed under many practical applications in computer industry; such as safety modeling, pre-planning building architectures, urban modeling and entertainment software. Most of these existing simulations are created by implementing computer algorithms based on extending deterministic models such as particle systems, clustering, cellular automata and fluid motion. However, extending a crowd model to simulate uncertainty of crowd behaviour during panic still remains a key challenge; since a computer algorithm approaches a solution by parameterizing predictable elements within a problem. It is evident from literature about the proven success of multi-agent technology behind modeling complex systems; comprising of many distributed entities interacting with each other and operated under lot of uncertainty. Thus it can be postulated that multiagent technology provides a basis to model the uncertainty raised within a crowd during panic. Our proposed solution simulates this uncertainty by considering evacuation of a crowd from a building during fire. Each individual in the crowd is modeled as an agent associated with a local ontology. The local ontology of an agent is a collection of rules, representing the knowledge known to each individual prior to occurring fire. Rules embedded within local ontologies are shared among individuals as they interact with each other. As a result non-anticipated global behaviours arise within the crowd leading to emerging uncertainty during fire. Output of the system is a visualization of crowd behaviour during fire with recorded statistics. The statistics recorded during each simulation session indicate evacuation related information per each individual; providing a basis for evaluation by comparison with real world observations.