Running Cells with Decision-Making Mechanism: Intelligence Decision P System for Evacuation Simulation
Abstract
Cell migration is a central process which happens along with multicellular organisms' development and maintenance. The process that cells move to specidic locations in particular directions has some similarities with pedestrian walking behaviour. In this work, we propose a simulation model called an Intelligence Decision P System (IDPS), which is inspired by the process of cell migration. Each cell has its own decision-making mechanism and moving mechanism. They move towards its goals on a two-dimensional space under the guidance of external signals and its own regulations. Cells also communicate with each other according to specidic interaction mechanism. The environment is dedined as a place for cell movement. It includes signal objects, some of which help start or end the migration and others have great influence on the speed and directions of cells. It also keeps a record of current position for each cell. Comparing with traditional P systems, cells can be considered as intelligent particles with decision-making mechanism and they can move to their destination. A case study is about modeling and simulating a building evacuation problem in a dire emergency by using the IDPS model. To our best knowledge, the topic of evacuation simulation was not under study in the dield of membrane computing before. The simulation result shows that the IDPS allows much easier and more precise modelling of pedestrian evacuation problems. So it is supposed to be a good simulation model for pedestrian walking behaviour.References
Alhazov, A.; Martin-Vide, C.; Pan, L. (2003); Solving a PSPACE-complete problem by recognizing P systems with restricted active membranes, Fundamenta Informaticae, 58(2), 66-77, 2003.
Barbuti, R.; Bove, P.; Milazzo, P.; Pardini, G. (2015), Minimal probabilistic P systems for modelling ecological systems, Theoretical Computer Science, 608, 36-56, 2015. https://doi.org/10.1016/j.tcs.2015.07.035
Barbuti, R.; Maggiolo-Schettini, A.; Milazzo, P.; Pardini, G.; Tesei, L. (2011); Spatial P systems, Nat Comput, 10, 3-16, 2011. https://doi.org/10.1007/s11047-010-9187-z
Bernardini, F.; Gheorghe, M. (2004); Population P Systems, Journal of Universal Computerence, 10(5), 509-539, 2004.
Besozzi, D.; Mauri, G.; P un, G. (2003); Gemmating P systems: collapsing hierarchies, Theoretical Computer Science, 296(2), 253-267, 2003. https://doi.org/10.1016/S0304-3975(02)00657-6
Blue, V.J.; Adler, J.L. (2001); Cellular automata microsimulation for modeling bidirectional pedestrian walkways, Transportation Research Part B Methodological, 35(3), 293-312, 2001. https://doi.org/10.1016/S0191-2615(99)00052-1
Ciobanu, G.; Pérez-Jiménez, M.J.; P un, G. eds. (2006); Applications of membrane computing, Springer Berlin Heidelberg, 287(1), 73-100, 2006.
Chalmet, L.G.; Francis, R.L.; Saunders, P.B. (1982); Network Models for Building Evacuation, Fire Technology, 18(1), 90-113, 1982. https://doi.org/10.1007/BF02993491
Fu, Y.W.; Liang, J.H.; Liu, Q.P.; Hu, X.Q. (2015); Crowd Simulation for Evacuation Behaviors Based on Multi-agent System and Cellular Automaton, International Conference on Virtual Reality and Visualization., 103-109, 2015.
Gómez, N.P.; O'Brien, K.; Silverman, B.G.; Badler, N.I. (2005); Crowd Simulation Incorporating Agent Psychological Models, Roles and Communication, First International Workshop on Crowd Simulation, 21-30, 2005.
Helbing, D.; Johansson, A.; Al-Abideen, H.Z. (2007); Dynamics of crowd disasters: an empirical study, Phys. Rev. E - Statist., Nonlin., Soft Matter Phys, 75(4), 1-7, 2007.
Helbing, D.; Molnar, P. (1995); Social force model for pedestrian dynamics, Phys. Rev. E, 51(5), 4282-4286, 1995. https://doi.org/10.1103/PhysRevE.51.4282
Hinze, T.; Weber, L.L.; Hatnik, U. (2016); Walking membranes: grid-exploring P systems with artificial evolution for multi-purpose topological optimisation of cascaded processes, International Conference on Membrane Computing, 251-271, 2016.
Hoogendoorn, S.; Bovy, P.H.L. (2003); Simulation of pedestrian flows by optimal control and differential games, Optimal Control Applications & Methods, 24 (3), 153-172, 2003. https://doi.org/10.1002/oca.727
Hughes, R.L. (2002); A continuum theory for the flow of pedestrians, Transportation Research Part B, 36(6), 507-535, 2002. https://doi.org/10.1016/S0191-2615(01)00015-7
Ionescu, M.; P un, G.; Yokomori, T. (2006); Spiking Neural P Systems, Fundamenta Informaticae, 71, 279-308, 2006.
Ibrahim, A.M.; Venkat, I.; Wilde, P.D. (2017); Uncertainty in a spatial evacuation model, Physica A Statistical Mechanics & Its Applications, 479, 485-497, 2017. https://doi.org/10.1016/j.physa.2017.03.024
Junaedi, H.; Hariadi, M.; Purnama, I.K.E. (2013); Multi agent with multi behavior based on particle swarm optimization (PSO) for crowd movement in fire evacuation, International Conference on Intelligent Control & Information Processing, 366-372, 2013.
Lovreglio, R.; Ronchi, E.; Nilsson, D. (2016); An Evacuation Decision Model based on perceived risk, social influence and behavioural uncertainty, Simulation Modelling Practice & Theory, 66, 226-242, 2016. https://doi.org/10.1016/j.simpat.2016.03.006
Pan, L.; P un, G.; Pérez-Jiménez, M.J. (2011); Spiking neural P systems with neuron division and budding, Science China Information Science, 54(8), 1596-1607, 2011. https://doi.org/10.1007/s11432-011-4303-y
P un, G. (2000); Computing with membranes, Journal of Computer and System Sciences, 61(1), 108-143, 2000. https://doi.org/10.1006/jcss.1999.1693
Paun, G.; Rozenberg, G.; Salomaa A. (2009); The Oxford Handbook of Membrane Computing, Oxford University Press, 2009.
Petre, I.; Petre, L. (2001); Mobile Ambients and P-Systems, Turku Centre for Computer Science, 2001.
Predtechenskii, V.M.; Milinskii, A.I. (1978); Planning for Foot Traffic Flow in Buildings NBS, Fire Technology, 1978.
Ronchi, E.; Nilsson, D.; Gwynne, S.M.V. (2012); Modelling the Impact of Emergency Exit Signs in Tunnels, Fire Technology, 48(4), 961-988, 2012. https://doi.org/10.1007/s10694-012-0256-y
Sakellariou, I.; Stamatopoulou, I.; Kefalas, P. (2012); Using membranes to model a multiagent system towards underground metro station crowd behaviour simulation, ECAI 2012 workshop. Montpellier, France, August, 28, 5-10, 2012.
Schadschneider, A.; Seyfried, A. (2010); Empirical results for pedestrian dynamics and their implications for cellular automata models, Networks & Heterogeneous Media, 6(3), 545-560, 2010.
Shi, J.; Ren, A.; Chen, C. (2009); Agent-based evacuation model of large public buildings under fire conditions, Automation in Construction, 18(3), 338-347, 2009. https://doi.org/10.1016/j.autcon.2008.09.009
Tan, L.; Hu, M.; Lin, H. (2015); Agent-based simulation of building evacuation: Combining human behavior with predictable spatial accessibility in a fire emergency, Information Sciences, 295, 53-66, 2015. https://doi.org/10.1016/j.ins.2014.09.029
Wagner, N.; Agrawal, V. (2014); An agent-based simulation system for concert venue crowd evacuation modeling in the presence of a fire disaster, Expert Systems with Applications, 41(6), 2807-2815, 2014. https://doi.org/10.1016/j.eswa.2013.10.013
Yuan, W.; Tan, K.H. (2007); An evacuation model using cellular automata, Physica A: Statistical Mechanics and its Applications, 384(2), 549-566, 2007. https://doi.org/10.1016/j.physa.2007.05.055
Zhang, G.; Liu, C.; Rong, H. (2010); Analyzing radar emitter signals with membrane algorithms, Mathematical and Computer Modelling, 52(11-12), 1997-2010, 2010. https://doi.org/10.1016/j.mcm.2010.06.002
Zhang, G.; Rong, H.; Cheng, J.; Qin, Y. (2014); A population-membrane-system-inspired evolutionary algorithm for distribution network reconfiguration, J. Electron, 23(3), 437-441, 2014.
Zhang, X.; Li, J.; Zhang, L. (2016); A multi-objective membrane algorithm guided by the skin membrane, Nat. Comput, 15(4), 597-610, 2016. https://doi.org/10.1007/s11047-016-9572-3
Zhang, X.; Li, X.; Mehaffey, J., Hadjisophocleous G. (2017); A probability-based Monte Carlo life-risk analysis model for fire emergencies, Fire Safety Journal, 89, 51-62, 2017. https://doi.org/10.1016/j.firesaf.2017.02.003
Zhang, X.; Wang, S.; Niu, Y.; Pan, L. (2011); Tissue P systems with cell separation: attacking the partition problem, Science China Information Sciences, 54(2), 293-304, 2011. https://doi.org/10.1007/s11432-010-4162-y
Zhang, G.; Gheorghe, M.; Pérez-Jiménez, M.J. (2017); Real-life Applications with Membrane Computing, Springer International Publishing, 2017.
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