KILT: A Modelling Approach Based on Participatory Agent-Based Simulation of Stylized Socio-Ecosystems to Stimulate Social Learning with Local Stakeholders | SpringerLink
Skip to main content
Springer Nature Link
Log in

KILT: A Modelling Approach Based on Participatory Agent-Based Simulation of Stylized Socio-Ecosystems to Stimulate Social Learning with Local Stakeholders

  • Conference paper
  • First Online:
Autonomous Agents and Multiagent Systems (AAMAS 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10643))

Included in the following conference series:

Abstract

A new approach is introduced under the slogan «Keep It a Learning Tool» (KILT) to emphasize the crucial need to make the purpose of the modelling process explicit when choosing the degree of complicatedness of an agent-based simulation model. We suggest that a co-design approach driven by early-stage and interactive simulation of empirical agent-based models representing stylized socio-ecosystems stimulates collective learning and, as a result, may promote the emergence of cooperative interactions among local stakeholders.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
¥17,985 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
JPY 3498
Price includes VAT (Japan)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
JPY 5719
Price includes VAT (Japan)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
JPY 7149
Price includes VAT (Japan)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

Notes

  1. 1.

    http://ccl.northwestern.edu/netlogo/models/HubNetGridlockHubNet.

References

  1. Crookall, D., Martin, A., Saunders, D., Coote, A.: Human and computer involvement in simulation. Simul. Gaming 17, 345–375 (1986)

    Google Scholar 

  2. Bousquet, F., Barreteau, O., D’Aquino, P., Etienne, M., Boissau, S., Aubert, S., Le Page, C., Babin, D., Castella, J.-C.: Multi-agent systems and role games: collective learning processes for ecosystem management. In: Janssen, M.A. (ed.) Complexity and Ecosystem Management. The Theory and Practice of Multi-Agent Systems, pp. 248–285. Edward Elgar Publishing, Cheltenham (2002)

    Google Scholar 

  3. Barreteau, O., Le Page, C., Perez, P.: Contribution of simulation and gaming to natural resource management issues: an introduction. Simul. Gaming 38, 185–194 (2007)

    Article  Google Scholar 

  4. Barreteau, O., Le Page, C., D’Aquino, P.: Role-playing games, models and negotiation processes. J. Artif. Soc. Soc. Simul. 6(2), 10 (2003)

    Google Scholar 

  5. Barreteau, O.: The joint use of role-playing games and models regarding negotiation processes: characterization of associations. J. Artif. Soc. Soc. Simul. 6(2), 3 (2003)

    Google Scholar 

  6. Le Page, C., Abrami, G., Barreteau, O., Becu, N., Bommel, P., Botta, A., Dray, A., Monteil, C., Souchère, V.: Models for sharing representations. In: Etienne, M. (ed.) Companion Modelling. A Participatory Approach to Support Sustainable Development, pp. 69–96. Quæ, Versailles (2011)

    Google Scholar 

  7. Berland, M., Rand, W.: Participatory simulation as a tool for agent-based simulation. In: ICAART 2009: Proceedings of the International Conference on Agents and Artificial Intelligence, pp. 553–557 (2009)

    Google Scholar 

  8. Guyot, P., Honiden, S.: Agent-based participatory simulations: merging multi-agent systems and role-playing games. J. Artif. Soc. Soc. Simul. 9(4), 8 (2006)

    Google Scholar 

  9. Guyot, P., Drogoul, A., Honiden, S.: Power and negotiation: lessons from agent-based participatory simulations. In: Fifth International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2006), pp. 27–33 (2006)

    Google Scholar 

  10. Wilensky, U., Stroup, W.: Learning through participatory simulations: network-based design for systems learning in classrooms. In: Proceedings of the Computer Supported Collaborative Learning Conference (CSCL 1999), pp. 667–676. Lawrence Erlbaum Associates, Mahwah (1999)

    Google Scholar 

  11. Wilensky, U., Stroup, W.: NetLogo HubNet Gridlock HubNet model. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL (1999)

    Google Scholar 

  12. Colella, V.: Participatory simulations: building collaborative understanding through immersive dynamic modeling. J. Learn. Sci. 9, 471–500 (2000)

    Article  Google Scholar 

  13. Boissau, S., Lan Anh, H., Castella, J.C.: The SAMBA role play game in Northern Vietnam. Mt. Res. Dev. 24, 101–105 (2004)

    Article  Google Scholar 

  14. Castella, J.C., Trung, T.N., Boissau, S.: Participatory simulation of land-use changes in the Northern Mountains of Vietnam: the combined use of an agent-based model, a role-playing game, and a geographic information system. Ecol. Soc. 10(1), 27 (2005)

    Article  Google Scholar 

  15. Le Page, C., Dray, A., Perez, P., Garcia, C.: Exploring how knowledge and communication influence natural resources management with REHAB. Simul. Gaming 47, 257–284 (2016)

    Article  Google Scholar 

  16. Mathevet, R., Le Page, C., Etienne, M., Lefebvre, G., Poulin, B., Gigot, G., Proréol, S., Mauchamp, A.: ButorStar: a role-playing game for collective awareness of reedbed wise use. Simul. Gaming 38, 233–262 (2007)

    Article  Google Scholar 

  17. Etienne, M.: SYLVOPAST a multiple target role-playing game to assess negotiation processes in silvopastoral management planning. J. Artif. Soc. Soc. Simul. 6(2), 5 (2003)

    Google Scholar 

  18. Rates, C.A., Mulvey, B.K., Feldon, D.F.: Promoting conceptual change for complex systems understanding: outcomes of an agent-based participatory simulation. J. Sci. Educ. Technol. 25(4), 610–627 (2016)

    Article  Google Scholar 

  19. Becu, N., Frascaria-Lacoste, N., Latune, J.: Distributed asymmetric simulation—enhancing participatory simulation using the concept of habitus. In: The Shift from Teaching to Learning: Individual, Collective and Organizational Learning Through Gaming Simulation, pp. 75–85 (2014)

    Google Scholar 

  20. Heppenstall, A., Crooks, A., See, L.M., Batty, M. (eds.): Agent-Based Models of Geographical Systems. Springer, Dordrecht (2012)

    Google Scholar 

  21. Crooks, A.: Agent-based models and geographical information systems. In: Brunsdon, C., Singleton, A. (eds.) Geocomputation: A Practical Primer, pp. 63–77. SAGE, London (2015)

    Google Scholar 

  22. Ligtenberg, A., Bregt, A.K., Van Lammeren, R.: Multi-actor-based land use modelling: spatial planning using agents. Landscape Urban Plann. 56, 21–33 (2001)

    Article  Google Scholar 

  23. Gimblett, H.R.: Integrating Geographic Information Systems and Agent-Based Modeling Techniques for Simulating Social and Ecological Processes. Oxford University Press, New York (2002)

    Google Scholar 

  24. Brown, D.G., Riolo, R., Robinson, D.T., North, M., Rand, W.: Spatial process and data models: toward integration of agent-based models and GIS. J. Geogr. Syst. 7, 25–47 (2005)

    Article  Google Scholar 

  25. Taillandier, P., Vo, D.-A., Amouroux, E., Drogoul, A.: GAMA: a simulation platform that integrates geographical information data, agent-based modeling and multi-scale control. In: Desai, N., Liu, A., Winikoff, M. (eds.) PRIMA 2010. LNCS, vol. 7057, pp. 242–258. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-25920-3_17

    Chapter  Google Scholar 

  26. Langlois, P., Blanpain, B., Daudé, E.: MAGéo, une plateforme de modélisation et de simulation multi-agent pour les sciences humaines. Cybergeo Eur. J. Geogr. (2015). http://cybergeo.revues.org/27236

  27. Schlüter, M., McAllister, R.R.J., Arlinghaus, R., Bunnefeld, N., Eisenack, K., Hölker, F., Milner-Gulland, E.J., Müller, B., Nicholson, E., Quaas, M., Stöven, M.: New horizons for managing the environment: a review of coupled social-ecological systems modeling. Nat. Resour. Model. 25, 219–272 (2012)

    Article  MathSciNet  Google Scholar 

  28. Mathevet, R., Le Page, C., Etienne, M., Poulin, B., Lefebvre, G., Cazin, F., Ruffray, X.: Des roselières et des hommes. ButorStar: un jeu de rôles pour l’aide à la gestion collective. Rev. Int. Géomatique 18, 375–395 (2008)

    Article  Google Scholar 

  29. Gourmelon, F., Chlous-Ducharme, F., Kerbiriou, C., Rouan, M., Bioret, F.: Role-playing game developed from a modelling process: a relevant participatory tool for sustainable development? A co-construction experiment in an insular biosphere reserve. Land Use Policy 32, 96–107 (2013)

    Article  Google Scholar 

  30. Gourmelon, F., Rouan, M., Lefevre, J.-F., Rognant, A.: Role-playing game and learning for young people about sustainable development stakes: an experiment in transferring and adapting interdisciplinary scientific knowledge. J. Artif. Soc. Soc. Simul. 14(4), 21 (2011)

    Article  Google Scholar 

  31. Ören, T.I.: Uses of simulation. In: Sokolowski, J.A., Banks, C.M. (eds.) Principles of Modeling and Simulation, pp. 153–179. John Wiley & Sons (2008)

    Google Scholar 

  32. Sun, Z., Lorscheid, I., Millington, J.D., Lauf, S., Magliocca, N.R., Groeneveld, J., Balbi, S., Nolzen, H., Müller, B., Schulze, J., Buchmann, C.M.: Simple or complicated agent-based models? A complicated issue. Environ. Model Softw. 86, 56–67 (2016)

    Article  Google Scholar 

  33. Lusiana, B., van Noordwijk, M., Suyamto, D., Mulia, R., Joshi, L., Cadisch, G.: Users’ perspectives on validity of a simulation model for natural resource management. Int. J. Agric. Sustain. 9, 364–378 (2011)

    Google Scholar 

  34. Edmonds, B., Moss, S.: From KISS to KIDS – an ‘Anti-simplistic’ modelling approach. In: Davidsson, P., Logan, B., Takadama, K. (eds.) MABS 2004. LNCS, vol. 3415, pp. 130–144. Springer, Heidelberg (2005). https://doi.org/10.1007/978-3-540-32243-6_11

    Chapter  Google Scholar 

  35. Grimm, V., Revilla, E., Berger, U., Jeltsch, F., Mooij, W.M., Railsback, S.F., Thulke, H.-H., Weiner, J., Wiegand, T., DeAngelis, D.L.: Pattern-oriented modeling of agent-based complex systems: lessons from ecology. Science 310, 987–991 (2005)

    Article  Google Scholar 

  36. Axelrod, R.: Advancing the art of simulation in the social sciences. In: Conte, R., Hegselmann, R., Terna, P. (eds.) Simulating Social Phenomena. Lecture Notes in Economics and Mathematical Systems, vol. 456, pp. 21–40. Springer, Heidelberg (1997). https://doi.org/10.1007/978-3-662-03366-1_2

    Chapter  Google Scholar 

  37. Kilvington, M.J.: Building capacity for social learning in environmental management. Ph.D. Lincoln University, Canterbury, New Zealand (2010)

    Google Scholar 

  38. Reed, M., Evely, A., Cundill, G., Fazey, I., Glass, J., Laing, A., Newig, J., Parrish, B., Prell, C., Raymond, C., Stringer, L.: What is social learning? Ecol. Soc. 15(4), r1 (2010)

    Article  Google Scholar 

  39. Habermas, J.: The Theory of Communicative Action, vol. I. Beacon, Boston (1984)

    Google Scholar 

  40. Daré, W.S., Van Paassen, A., Ducrot, R., Mathevet, R., Queste, J., Trébuil, G., Barnaud, C., Lagabrielle, E.: Learning about interdependencies and dynamics. In: Etienne, M. (ed.) Companion Modelling. A Participatory Approach to Support Sustainable Development, pp. 205–229. Quæ, Versailles (2011)

    Google Scholar 

  41. Bouwen, R., Taillieu, T.: Multi-party collaboration as social learning for interdependence: developing relational knowing for sustainable natural resource management. J. Commun. Appl. Soc. Psychol. 14, 137–153 (2004)

    Article  Google Scholar 

  42. Perrotton, A., de Garine Wichatitsky, M., Valls-Fox, H., Le Page, C.: My cattle and your park: co-designing a role-playing game with rural communities to promote multi-stakeholder dialogue at the edge of protected areas. Ecol. Soc. 22(1), 35 (2017)

    Article  Google Scholar 

  43. Hardy, P.-Y., Souchère, V., Dray, A., David, M., Sabatier, R., Kernéis, E.: Individual vs collective in public policy design, a cooperation example in the Marais Poitevin region. In: Sauvage, S., Sánchez-Pérez, J.M., Rizzoli, A.E. (eds.) 8th International Congress on Environmental Modelling and Software, Toulouse, France (2016)

    Google Scholar 

  44. Bommel, P., Bonnet, M.-P., Coudel, E., Haentjens, E., Kraus, C.N., Melo, G., Nasuti, S., Le Page, C.: Livelihoods of local communities in an Amazonian floodplain coping with global changes. From role-playing games to hybrid simulations to involve local stakeholders in participatory foresight study at territorial level. In: 8th International Congress on Environmental Modelling and Software, pp. 1140–1147 (2016)

    Google Scholar 

  45. Barnaud, C., Van Paassen, A.: Equity, power games, and legitimacy: dilemmas of participatory natural resource management. Ecol. Soc. 18(2), 21 (2013)

    Article  Google Scholar 

  46. Druckman, D., Ebner, N.: Onstage or behind the scenes? Relative learning benefits of simulation role-play and design. Simul. Gaming 39, 465–497 (2008)

    Article  Google Scholar 

  47. Muro, M., Jeffrey, P.: A critical review of the theory and application of social learning in participatory natural resource management processes. J. Environ. Plann. Manag. 51, 325–344 (2008)

    Article  Google Scholar 

  48. Scholz, G.: How participatory methods facilitate social learning in natural resource management. An exploration of group interaction using interdisciplinary syntheses and agent-based modeling, Osnabrück, Germany (2016)

    Google Scholar 

  49. Vennix, J.A.M.: Group Model Building: Facilitating Team Learning Using System Dynamics. Jonh Wiley & Sons Ltd., Chichester (1996)

    Google Scholar 

  50. Mathevet, R., Etienne, M., Lynam, T., Calvet, C.: Water management in the Camargue Biosphere Reserve: insights from comparative mental models analysis. Ecol. Soc. 16(1), 43 (2011)

    Article  Google Scholar 

  51. Scholz, G., Austermann, M., Kaldrack, K., Pahl-Wostl, C.: Evaluating group model building exercises: a method for comparing externalized mental models and group models. Syst. Dyn. Rev. 31, 28–45 (2015)

    Article  Google Scholar 

  52. Black, L.J.: When visuals are boundary objects in system dynamics work. Syst. Dyn. Rev. 29, 70–86 (2013)

    Article  Google Scholar 

  53. Black, L.J., Andersen, D.F.: Using visual representations as boundary objects to resolve conflict in collaborative model-building approaches. Syst. Res. Behav. Sci. 29, 194–208 (2012)

    Article  Google Scholar 

  54. Wilensky, U., Papert, S.: Restructurations: reformulations of knowledge disciplines through new representational forms. In: Constructionism 2010, Paris (2010)

    Google Scholar 

  55. Schlüter, M., Müller, B., Frank, K.: How to use models to improve analysis and governance of social-ecological systems-the reference frame MORE (2013)

    Google Scholar 

  56. Schusler, T.M., Decker, D.J., Pfeffer, M.J.: Social learning for collaborative natural resource management. Soc. Nat. Resour. 16, 309–326 (2003)

    Article  Google Scholar 

  57. Brugnach, M.: From prediction to learning: the implications of changing the purpose of the modelling activity. In: Proceedings of the iEMSs Fourth Biennial Meeting: International Congress on Environmental Modelling and Software (iEMSs 2010), pp. 547–553. International Environmental Modelling and Software Society (2010)

    Google Scholar 

  58. de Sartre, X.A., Petit, O.: L’interdisciplinarité comme méthode de compréhension des interactions entre natures et sociétés. In: Hubert, B., Mathieu, N. (eds.) Interdisciplinarités entre Natures et Sociétés, pp. 367–386. P.I.E. Peter Lang, Bruxelles (2016)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. CIRAD, UPR Green, 34398, Montpellier, France

    Christophe Le Page

  2. CIRAD, UPR Green, University of Brasilia, Brasilia, Brazil

    Christophe Le Page

  3. CIRAD, UMR Astre, 34398, Montpellier, France

    Arthur Perrotton

  4. Center for Applied Social Sciences, University of Zimbabwe, Harare, Zimbabwe

    Arthur Perrotton

Authors
  1. Christophe Le Page
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Arthur Perrotton
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Christophe Le Page or Arthur Perrotton .

Editor information

Editors and Affiliations

  1. University of Central Florida, Orlando, Florida, USA

    Gita Sukthankar

  2. IIIA-CSIC, Bellaterra, Spain

    Juan A. Rodriguez-Aguilar

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Le Page, C., Perrotton, A. (2017). KILT: A Modelling Approach Based on Participatory Agent-Based Simulation of Stylized Socio-Ecosystems to Stimulate Social Learning with Local Stakeholders. In: Sukthankar, G., Rodriguez-Aguilar, J. (eds) Autonomous Agents and Multiagent Systems. AAMAS 2017. Lecture Notes in Computer Science(), vol 10643. Springer, Cham. https://doi.org/10.1007/978-3-319-71679-4_3

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-71679-4_3

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-71678-7

  • Online ISBN: 978-3-319-71679-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation