This paper proposes the use of methods for network analysis in order to study the properties of a dynamic graph that model the interaction among agents in an agent-based model. This model is based on Multi Agent System definition and simulates a multicultural crowd in which proxemics theory and distance perception are taking into account. After a discussion about complex network analysis and crowd research context, an agent-based model based on SCA*PED (Situated Cellular Agents for PEdestrian Dynamics) approach is presented, based on two separated yet interconnected layers representing different aspects of the overall system dynamics. Then, an analysis of network derived from agent interactions in the Proxemic layer is proposed, identifying characteristic structures and their meaning in the crowd analysis. At the end an analysis related to the identification of those characteristic structures in some real examples is proposed.
Manenti, L., Manzoni, L., Manzoni, S. (2010). Towards an Application of Graph Structure Analysis to a MAS-based Model of Proxemic Distances in Pedestrian Systems. In 11th Workshop on Objects to Agents, WOA 2010; Rimini; Italy; 5-7 September 2010.
Towards an Application of Graph Structure Analysis to a MAS-based Model of Proxemic Distances in Pedestrian Systems
MANENTI, LORENZA ALESSANDRAPrimo
;MANZONI, LUCASecondo
;MANZONI, SARA LUCIAUltimo
2010
Abstract
This paper proposes the use of methods for network analysis in order to study the properties of a dynamic graph that model the interaction among agents in an agent-based model. This model is based on Multi Agent System definition and simulates a multicultural crowd in which proxemics theory and distance perception are taking into account. After a discussion about complex network analysis and crowd research context, an agent-based model based on SCA*PED (Situated Cellular Agents for PEdestrian Dynamics) approach is presented, based on two separated yet interconnected layers representing different aspects of the overall system dynamics. Then, an analysis of network derived from agent interactions in the Proxemic layer is proposed, identifying characteristic structures and their meaning in the crowd analysis. At the end an analysis related to the identification of those characteristic structures in some real examples is proposed.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.