Situated Cellular Agents: A Model to Simulate Crowding Dynamics

SUMMARY This paper presents a Multi Agent Systems (MAS) approach to crowd modelling, based on the Situated Cellular Agents (SCA) model. This is a special class of Multilayered Multi Agent Situated System (MMASS), providing an explicit representation of spatial structures and dieren t means of agent interaction. Heterogenous agents may be obtained through the denition of dieren t agent types, specifying dieren t behaviours and perceptive capabilities. The model is rooted on some basic principles of Cellular Automata (e.g. the denition of adjacency geometries), but also takes into account the autonomy of modelled entities, with their own internal architecture. A formal denition of the SCA model will be given, with a description of how it can be applied to forward and backward approaches to simulation. Particular attention will be paid to the crowd and pedestrian modelling, and two applications to simulation to

[1]  Stefania Bandini,et al.  Dealing with space in multi--agent systems: a model for situated MAS , 2002, AAMAS '02.

[2]  Joshua M. Epstein,et al.  Growing artificial societies , 1996 .

[3]  Harry J. P. Timmermans,et al.  A Multi-Agent Cellular Automata System for Visualising Simulated Pedestrian Activity , 2000, ACRI.

[4]  Jaime Simão Sichman,et al.  Multi-Agent-Based Simulation , 2002, Lecture Notes in Computer Science.

[5]  Michael Schreckenberg,et al.  Pedestrian and evacuation dynamics , 2002 .

[6]  Scott Moss,et al.  Proceedings of the Second International Workshop on Multi-Agent-Based Simulation-Revised and Additional Papers , 2000 .

[7]  Jaime Simão Sichman,et al.  Multi-Agent-Based Simulation, Third International Workshop, MABS 2002, Bologna, Italy, July 15-16, 2002, Revised Papers , 2003, MABS.

[8]  Michael R. Genesereth,et al.  Logical foundations of artificial intelligence , 1987 .

[9]  Bin Jiang,et al.  AGENT-BASED APPROACH TO MODELLING ENVIRONMENTAL AND URBAN SYSTEMS WITHIN GIS , 2000 .

[10]  Dirk Helbing,et al.  A mathematical model for the behavior of pedestrians , 1991, cond-mat/9805202.

[11]  H. Van Dyke Parunak,et al.  The Process-Interface-Topology Model: Overlooked Issues in Modeling Social Systems , 2000 .

[12]  A. Schadschneider Cellular Automaton Approach to Pedestrian Dynamics - Theory , 2001, cond-mat/0112117.

[13]  Alberto RibesAbstract,et al.  Multi agent systems , 2019, Proceedings of the 2005 International Conference on Active Media Technology, 2005. (AMT 2005)..

[14]  Pascal Perez MULTI-AGENT BASED SIMULATION (MABS) , 2003 .

[15]  Helen Couclelis,et al.  From Cellular Automata to Urban Models: New Principles for Model Development and Implementation , 1997 .

[16]  Nigel Gilbert,et al.  Multi-Agent Systems and Agent-Based Simulation , 1998, Lecture Notes in Computer Science.

[17]  Stephen Wolfram,et al.  Theory and Applications of Cellular Automata , 1986 .

[18]  Dirk Helbing A Fluid-Dynamic Model for the Movement of Pedestrians , 1992, Complex Syst..

[19]  J. Zittartz,et al.  Cellular Automaton Approach to Pedestrian Dynamics - Applications , 2001, cond-mat/0112119.

[20]  P. Torrens,et al.  Cellular Automata and Urban Simulation: Where Do We Go from Here? , 2001 .

[21]  Jacob Goldenberg,et al.  Using Complex Systems Analysis to Advance Marketing Theory Development , 2001 .

[22]  Franco Zambonelli,et al.  Engineering Societies in the Agents World , 2000, Lecture Notes in Computer Science.

[23]  Jacques Ferber,et al.  Using reactive multi-agent systems in simulation and problem solving , 1992 .

[24]  H. Van Dyke Parunak,et al.  Distinguishing Environmental and Agent Dynamics: A Case Study in Abstraction and Alternate Modeling Technologies , 2000, ESAW.

[25]  岡崎 甚幸,et al.  建築空間における歩行のためのシミュレーションモデルの研究 : その 1 磁気モデルの応用による歩行モデル , 1979 .