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Exploring behavioral regions in agents’ mental maps

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“‘Sometimes you repeat yourself, man.’ ‘It’s in my nature’.” (1984, p. 80)

Abstract

Agent-based models continue to grow more sophisticated at the individual scale of regional science inquiry, but it remains difficult to ally the intricacies of individual behavior in those models to regional phenomena and processes in anything but a loose fashion, leaving explanatory pathways between the scales quite slack. In this paper, we present a mechanism for bridging the gap between individual agency and regional outcomes of that agency in simulation. We use agents to develop very rich behavioral understanding of their surroundings in simulation. We then sweep through the information that agents generate when determining how to execute their transition rules, using schemes that mine agent states to produce mental maps of varied aspects of their dynamics. From agents’ mental maps, we define and visualize regions as geographies that are conjured from the unique, autonomous, local, and personal insight that agents can provide. We demonstrate the utility of the scheme, with application to indoor movement scenarios in which fleeting regions form amid agents interactions with each other and their built surroundings. Our approach is extensible beyond these applications and could be of broader use for other explorative scenarios in regional science.

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References

  • Arthur WB (1990) Positive feedbacks in the economy. Sci Am 262(2):80–85

  • Badler NI, Bindiganavale R, Granieri JP, Wei S, Zhao Z (1994) Posture interpolation with collision avoidance. In: Anonymous (ed) Proceedings of computer animation’94, Geneva, May 25–28, Geneva: IEEE, pp 13–20

  • Badler NI, Manoochehri KH, Walters G (1987) Articulated figure positioning by multiple constraints. Comput Graph Appl 7(6):28–38

    Article  Google Scholar 

  • Batty M (2003) Agent-based pedestrian modelling. In: Longley PA, Batty M (eds) Advanced spatial analysis: the CASA book of GIS. ESRI Press, Redlands, pp 81–107

    Google Scholar 

  • Batty M (2005) Cities and complexity: understanding cities with cellular automata, agent-based models, and fractals. The MIT Press, Cambridge

    Google Scholar 

  • Batty M (2006) Rank clocks. Nature 444(7119):592–596

    Article  Google Scholar 

  • Batty M (2008) Fifty years of urban modeling: macro-statics to micro-dynamics. In: Albeverio S, Andrey D, Giordano P, Vancheri A (eds) The dynamics of complex urban systems. Physica-Verlag HD, Berlin, pp 1–20

    Chapter  Google Scholar 

  • Batty M, Longley PA, Fotheringham AS (1989) Urban growth and form: scaling, fractal geometry, and diffusion-limited-aggregation. Environ Plan A 21:1447–1472

    Article  Google Scholar 

  • Batty M, Torrens PM (2005) Modeling and prediction in a complex world. Futures 37(7):745–766

    Article  Google Scholar 

  • Batty M, Xie Y, Zhao K (2007) Simulating emergent urban form using agent-based modeling: Desakota in the Suzhou-Wuxian region in China. Ann Assoc Am Geogr 97(3):477–495

    Article  Google Scholar 

  • Benenson I, Omer I, Hatna E (2002) Entity-based modeling of urban residential dynamics: the case of Yaffo, Tel Aviv. Environ Plan B Plan Des 29:491–512

    Article  Google Scholar 

  • Benenson I, Torrens PM (2004) Geosimulation: automata-based modeling of urban phenomena. Wiley, London

    Book  Google Scholar 

  • Boltes M, Seyfried A, Steffen B, Schadschneider A (2010) Automatic extraction of pedestrian trajectories from video recordings. In: Klingsch WWF, Rogsch C, Schadschneider A, Schreckenberg M (eds) Pedestrian and evacuation dynamics 2008. Springer, Berlin, pp 43–54

    Chapter  Google Scholar 

  • Boyce DE (1988) Renaissance of large-scale models. Pap Reg Sci 65(1):1–10

    Article  Google Scholar 

  • Brown DG, Robinson DT (2006) Effects of heterogeneity in residential preferences on an agent-based model of urban sprawl. Ecol Soc 11(1):46–68

    Google Scholar 

  • Bukowski RW, Kuligowski ED (2004) Basis for Egress Provisions in US Building Codes. In: Interflam (ed) Tenth proceedings of international interflam conference, Edinburgh, Scotland, 5–7 July 2004, Greenwich, UK: Interscience Communications, pp 375–386

  • Chen J, Shaw S-L, Yu H, Lu F, Chai Y, Jia Q (2011) Exploratory data analysis of activity diary data: a space-time GIS approach. J Transp Geogr 19(3):394–404

    Article  Google Scholar 

  • Clark WA (1991) Residential preferences and neighborhood racial segregation: a test of the Schelling segregation model. Demography 28(1):1–19

    Article  Google Scholar 

  • Clark WAV (1993) Search and choice in urban housing markets. In: Gärling T, Golledge RG (eds) Behavior and environment: psychological and geographical approaches. Elsevier, North Holland, Amsterdam, pp 298–316

    Chapter  Google Scholar 

  • Daamen W, Hoogendoorn S (2003) Controlled experiments to derive walking behaviour. Eur J Transp Infrastruct Res 3(1):39–59

    Google Scholar 

  • Daamen W, Hoogendoorn SP (2004) Pedestrian traffic flow operations on a platform: observations and comparison with simulation tool SimPed. In: Allen J, Brebbia CA, Hill RJ, Sciutto G, Sone S (eds) Computers in railways IX (Congress proceedings of CompRail 2004), Dresden, Germany, May 2004. WIT Press, Southampton, pp 125–134

    Google Scholar 

  • Edelsbrunner H (1992) Weighted alpha shapes (unpublished paper, Department of Computer Science, Duke University). Duke University, Durham, NC

  • Edelsbrunner H, Kirkpatrick D, Seidel R (1983) On the shape of a set of points in the plane. IEEE Trans Inf Theory 29(4):551–559

    Article  Google Scholar 

  • Edelsbrunner H, Mücke EP (1994) Three-dimensional alpha shapes. ACM Trans Graph 13(1):43–72

    Article  Google Scholar 

  • Ericson C (2005) Real-time collision detection. Morgan Kauffman, Amsterdam

    Google Scholar 

  • Gibson W (1984) Neuromancer. Ace Books, New York

    Google Scholar 

  • Goffmann E (1963) Behavior in public places. Free Press, New York

    Google Scholar 

  • Goffmann E (1971) Relations in public: microstudies in the public order. Basic Books, New York

    Google Scholar 

  • Golledge R, Stimson RJ (1997) Spatial behavior: a geographic perspective. The Guilford Press, New York

    Google Scholar 

  • Golledge RA (1992) Place recognition and wayfinding: making sense of space. Geoforum 23(2):199–214

    Article  Google Scholar 

  • Golledge R (1999) Wayfinding behavior: cognitive mapping and other spatial processes. The Johns Hopkins Press, Baltimore

    Google Scholar 

  • Golledge RG (1981) Misconceptions, misinterpretations, and misrepresentations of behavioral approaches in human geography. Environ Plan A 13(11):1325–1344

    Article  Google Scholar 

  • Gould P, White R (1974) Mental maps. Routledge, New York

    Book  Google Scholar 

  • Hägerstrand T (1970) What about people in regional science? Pap Reg Sci 24(1):6–21

    Article  Google Scholar 

  • Hägerstrand T (1982) Diorama, path and project. Tijdschrift voor Economische en Sociale Geografie 73:323–339

    Article  Google Scholar 

  • Helbing D, Molnár P (1997) Self-organization phenomena in pedestrian crowds. In: Schweitzer F (ed) Self-organization of complex structures: from individual to collective dynamics. Gordon and Breach, London, pp 569–577

    Google Scholar 

  • Klosterman RE (1994) Large-scale urban models: retrospect and prospect. J Am Plan Assoc 60(1):3–6

    Article  Google Scholar 

  • Landis J (2001) CUF, CUF II, and CURBA: a family of spatially explicit urban growth and land-use policy simulation models. In: Brail RK, Klosterman RE (eds) Planning support systems: integrating geographic information systems, models, and visualization tools. ESRI Press, Redlands, CA, pp 157–200

    Google Scholar 

  • Latombe J-C (1991) Robot motion planning. Kluwer Academic Publishers, Norwell, MA

    Book  Google Scholar 

  • Mansury Y, Gulyas L (2007) The emergence of Zipf’s Law in a system of cities: an agent-based simulation approach. J Econ Dyn Contr 31(7):2438–2460

    Article  Google Scholar 

  • Mount DM, Silverman R (1990) Packing and covering the plane with translates of a convex polygon. J Algorithm 11(4):564–580

    Article  Google Scholar 

  • Nagel K, Schrekenberg M (1995) Traffic jams in stochastic cellular automata. Los Alamos National Laboratory, Los Alamos

    Google Scholar 

  • Nara A, Torrens PM (2007) Spatial and temporal analysis of pedestrian egress behavior and efficiency. In: Samet H, Shahabi C, Schneider M (eds) Association of computing machinery (ACM) advances in geographic information systems. Association of Computing Machinery, New York, pp 284–287

    Google Scholar 

  • Nara A, Torrens PM (2011) Trajectory data mining: classification and spatio-temporal visualization of mobile objects. In: Cheng T, Longley PA, Ellul C, Chow A (eds) Proceedings of geocomputation 2011, July 20–22, London. Geocomputation, London, pp 338–345

    Google Scholar 

  • Okabe A, Boots BN, Sugihara K, Chiu SN (1992) Spatial tessellations: concepts and applications of voronoi diagrams. Wiley, Chichester

    Google Scholar 

  • Reynolds CW (1987) Flocks, herds, and schools: a distributed behavioral model. Comput Graph 21(4):25–34

    Article  Google Scholar 

  • Reynolds CW (1999) Steering behaviors for autonomous characters. In: Proceedings of game developers conference. Miller Freeman Game Group, San Francisco, pp 763–782

  • Rollero C, De Piccoli N (2010) Place attachment, identification and environment perception: an empirical study. J Environ Psychol 30(2):198–205

    Article  Google Scholar 

  • Schweitzer F (2002) Modeling migration and economic agglomeration with active Brownian particles. In: Schweitzer F (ed) Modeling complexity in economic and social systems. World Scientific Publishing Company, Singapore, pp 137–161

    Chapter  Google Scholar 

  • Sipper M (1997) Evolution of parallel cellular machines: the cellular programming approach. Springer, Berlin

    Book  Google Scholar 

  • Slater-Hammel A (1955) Estimation of movement as a function of the distance of movement perception and target distance. Percept Mot Skills 5(3):201–204

    Article  Google Scholar 

  • Smith JH (1882) Exit from theaters. Google Patents, USA

    Google Scholar 

  • Stanley HE (2000) Non-equilibrium physics: freezing by heating. Nature 404(6779):718–719

    Article  Google Scholar 

  • Sumpter DJT (2006) The principles of collective animal behaviour. Philos Trans R Soc B Biol Sci 29(361):5–22

    Article  Google Scholar 

  • Takeyama M, Couclelis H (1997) Map dynamics: integrating cellular automata and GIS through geo-algebra. Int J Geogr Inf Syst 11(1):73–91

    Article  Google Scholar 

  • Tolani D, Goswami A, Badler NI (2000) Real-time inverse kinematics techniques for anthropomorphic limbs. Graph Model 62:353–388

    Article  Google Scholar 

  • Tomlin CD (1990) Geographic information systems and cartographic modeling. Prentice Hall College Divison, Englewood-Cliffs

    Google Scholar 

  • Tomlinson RF (1974) The application of electronic computing methods to the storage, compilation and assessment of mapped data. In: Unpublished Ph. D. thesis. London: Department of Geography, University of London, University College London

  • Torrens PM (2001) Where in the world? Exploring the factors driving place location knowledge among secondary level students in Dublin, Ireland. J Geogr 100(2):49–61

    Article  Google Scholar 

  • Torrens PM (2007a) Behavioral intelligence for geospatial agents in urban environments. In: Lin TY, Bradshaw JM, Klusch M, Zhang C (eds) IEEE intelligent agent technology (IAT 2007). IEEE, Los Alamitos, CA, pp 63–66

  • Torrens PM (2007b) A geographic automata model of residential mobility. Environ Plan B 33(2):200–222

    Article  Google Scholar 

  • Torrens PM (2010a) Agent-based modeling and the spatial sciences. Geogr Compass 4(5):428–448

    Article  Google Scholar 

  • Torrens PM (2010b) Geography and computational social science. Geo J 75(2):133–148

    Google Scholar 

  • Torrens PM (2012) Moving agent pedestrians through space and time. Ann Assoc Am Geogr 102(1):35–66

    Article  Google Scholar 

  • Torrens PM (2014) High-fidelity behaviours for model people on model streetscapes. Ann GIS 20(3):139–157

    Article  Google Scholar 

  • Torrens PM (2015a) Geographical agents in three dimensions. In: Singleton A, Brunsdon C (eds) Geocomput Prac Prim. Sage, London, pp 40–62

    Google Scholar 

  • Torrens PM (2015b) Slipstreaming human geosimulation in virtual geographic environments. Annals of GIS (Online first at http://www.tandfonline.com/doi/pdf/10.1080/19475683.2015.1009489):1-20

  • Torrens PM, Griffin WA (2013) Exploring the micro-social geography of children’s interactions in preschool: a long-term observational study and analysis using Geographic Information Technologies. Environ Behav 45(5):584–614

    Article  Google Scholar 

  • Torrens PM, Li X, Griffin WA (2011) Building agent-based walking models by machine-learning on diverse databases of space-time trajectory samples. Trans Geogr Inf Sci 15(s1):67–94

    Google Scholar 

  • Torrens PM, Nara A (2007) Modeling gentrification dynamics: a hybrid approach. Comput Environ Urban Syst 31(3):337–361

    Article  Google Scholar 

  • Torrens PM, Nara A (2013) Polyspatial agents for multi-scale urban simulation and regional policy analysis. Reg Sci Policy Pract 44(4):419–445

    Google Scholar 

  • Torrens PM, Nara A, Li X, Zhu H, Griffin WA, Brown SB (2012) An extensible simulation environment and movement metrics for testing walking behavior in agent-based models. Comput Environ Urban Syst 36(1):1–17

    Article  Google Scholar 

  • Tuan Y-F (1975a) Images and mental maps. Ann Assoc Am Geogr 65(2):205–212

    Article  Google Scholar 

  • Tuan Y-F (1975b) Place: an experiential perspective. Geogra Rev 65(2):151–165

  • van de Panne M (1997) From footprints to animation. Comput Graph Forum 16(4):211–223

    Article  Google Scholar 

  • Waddell PA, Borning A, Noth M, Freier N, Becke M, Ulfarsson G (2003) Microsimulation of urban development and location choices: design and implementation of UrbanSim. Netw Spat Econ 3(1):43–67

    Article  Google Scholar 

  • Zhao J, Badler NI (1994) Inverse kinematics positioning using nonlinear programming for highly articulated figures. ACM Trans Graph 13(4):313–336

    Article  Google Scholar 

Download references

Acknowledgments

This material is based in part upon work supported by the National Science Foundation under grant numbers 1340984, 1343123, and 1441177. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author and do not necessarily reflect the views of the National Science Foundation.

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Authors and Affiliations

  1. Geosimulation Research Laboratory, Department of Geographical Sciences, Center for Geospatial Information Science, Institute for Advanced Computer Studies (UMIACS), University of Maryland, College Park, MD, 20742, USA

    Paul M. Torrens

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  1. Paul M. Torrens
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Correspondence to Paul M. Torrens.

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Torrens, P.M. Exploring behavioral regions in agents’ mental maps. Ann Reg Sci 57, 309–334 (2016). https://doi.org/10.1007/s00168-015-0682-0

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