Water Resources Analysis: An Approach based on Agent-Based Modeling


  • Giovani Farias FURG
  • Bruna Leitzke FURG
  • Míriam Born UFPel
  • Marilton Aguiar UFPel
  • Diana Adamatti FURG




Multi-Agent Systems, Natural Resources, Agent-Based Model, GAMA


The paper aims to present a river basin modeling using GAMA platform for water resources analysis. Currently, several models based on multi-agent systems are used for natural resources management and they present satisfactory results for this type of scenario. GAMA is agents based and widely used in this context with several studies already published. In this study, the Sa ̃o Gonc ̧alo and Lagoa Mirim basins were considered from georeferenced data. In the modeling, regions, and rivers are agents on the system where rivers water can flow among neighbors regions.


Download data is not yet available.


FULLER, M. M. et al. Computational science for natural resource management. Computing in Science & Engineering, IEEE Computer Society, v. 9, n. 4, p. 40, 2007.

HOLZMAN, B. Natural Resource Mana- gement. 2009. [Online; accessed 30 apr. 2019] http://online.sfsu.edu/bholzman//courses/GEOG 20657/.

FILATOVA, T. et al. Spatial agent-based models for socio-ecological systems: Challenges and prospects. Environmental modelling & software, Elsevier, v. 45, p. 1–7, 2013.

ADAMATTI, D. F. Insercão de jogadores virtuais em jogos de papeis para uso em sistemas de apoio a decisao em grupo: um experimento no domınio da gestao de recursos naturais. Tese (Doutorado) — Escola Politecnica – Universidade de Sao Paulo, Sao Paulo, Brasil, 2007.

TAILLANDIER, P. et al. Building, composing and experimenting complex spatial models with the GAMA platform. GeoInformatica, Dec 2018.

PAGE, C. L. et al. Cormas: A multiagent simulation toolkit to model natural and social dynamics at multiple scales. International Conference of the Resource Modeling Associa- tion 2000 : The ecology of scales, Wageningen, p. 1–20, Jun 2000.

GAUDOU, B. et al. The MAELIA multi-agent platform for integrated analysis of interactions between agricultural land-use and low-water management strategies. In: ALAM, S. J.; PARUNAK, H. V. D. (Ed.). Multi-Agent-Based Simu- lation XIV. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. p. 85–100.

SECRETARIA do Meio Ambiente e Infraestrutura - L040 - Bacia Hidrografica da Lagoa Mirim e do Canal Sao Goncalo. 2019. Https://www.sema.rs.gov.br/l040-bacia- hidrografica-da-lagoa-mirim-e-do-canal-sao-goncalo [Online; accessed 31 mar. 2019].

BOUSQUET, F.; PAGE, C. L. Multi-agent simulations and ecosystem management: a review. Ecological modelling, Elsevier, v. 176, n. 3-4, p. 313–332, 2004.

COPPIN, B. Inteligencia Artificial. 3. ed. Rio de Janeiro: LTC, 2010.

WOOLDRIDGE, M. An introduction to multi agent systems, Department of Computer Science, University of Liverpool, uk. John Wiley & Sons, Ltd, 2002.

BORDINI, R. H.; VIEIRA, R.; MOREIRA, A. F. Fundamentos de sistemas multiagentes. v. 2, p. 3–41, 2001.

ALVARES, L. O.; SICHMAN, J. S. Introducao aos sistemas multiagentes. Brasilia - UnB, p. 1–37, 1997.

HUBNER, J. F.; BORDINI, R. H.; VIEIRA, R. Introducao ao desenvolvimento de sistemas multiagentes com jason. XII Escola de Informatica da SBC, v. 2, p. 51–89, 2004.

SANTOS, F. P. D. et al. A multiagent-based tool for the simulation of social production and management of urban ecosystems: a case study on san jero ́nimo vegetable garden- seville, spain. Journal of Artificial Societies and Social Simu- lation, Journal of Artificial Societies and Social Simulation, v. 19, n. 3, p. 1–12, 2016.

BOISSIER, O. et al. Multi-agent oriented programming with JaCaMo. Science of Computer Programming, 2011.

BORDINI, R. H.; HuBNER, J. F.; WOOLDRIDGE, M. Programming multi-agent systems in agentspeak using jason. John Wiley & Sons, 2007.

RICCI, A. et al. Environment programming in CArtAgO. Springer, p. 259–288, 2009.

Hu ̈BNER, J. F.; SICHMAN, J. S.; BOISSIER, O. De- veloping organised multiagent systems using the MOISE+ model: programming issues at the system and agent levels. Int. J. Agent-Oriented Software Engineering, v. 1, n. 3/4, p. 370–395, 2007.

LI, G. et al. Water-energy-food nexus in urban sustainable development: an agent-based model. International Journal of Crowd Science, Emerald Publishing Limited, v. 1, n. 2, p. 121–132, 2017.

Le Page, C. et al. Exploring how knowledge and communication influence natural resources management with ReHab. Simulation & Gaming, SAGE Publications Inc., v. 47, n. 2, p. 257–284, apr 2016.

ADAMATTI, D. F.; SICHMAN, J. S.; COELHO, H. An analysis of the insertion of virtual players in GMABS methodology using the ViP-JogoMan prototype. Journal of Artificial Societies and Social Simulation, v. 12, n. 3, 2009.

CAMPO, P. C. et al. Exploring management strategies for community-based forests using multi-agent systems: A case study in Palawan, Philippines. Journal of Environmental Management, v. 90, n. 11, p. 3607–3615, aug 2009.

̈ ́

FAROLFI, S.; MULLER, J.-P.; BONTE, B. An iterative

construction of multi-agent models to represent water supply and demand dynamics at the catchment level. Environmental Modelling & Software, v. 25, n. 10, p. 1130–1148, oct 2010.

RUANKAEW, N. et al. Companion modelling for inte- grated renewable resource management: a new collaborative approach to create common values for sustainable develop- ment. International Journal of Sustainable Development & World Ecology, v. 17, n. 1, p. 15–23, feb 2010.


SOUCHERE, V. et al. Co-constructing with stakeholders a role-playing game to initiate collective management of erosive runoff risks at the watershed scale. Environmental Modelling & Software, v. 25, n. 11, p. 1359–1370, nov 2010.

GOURMELON, F. et al. 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, v. 32, p. 96–107, may 2013.

Le Page, C. et al. Companion modelling with rice farmers to characterise and parameterise an agent-based model on the land/water use and labour migration in northeast Thailand. In: Empirical Agent-Based Modelling - Challenges and Solutions. New York, NY: Springer, 2014. p. 207–221.

REBAUDO, F. et al. Agent-based models and integrated pest management diffusion in small scale farmer communities. In: Integrated Pest Management. Dordrecht: Springer Netherlands, 2014. p. 367–383.

Le Page, C.; PERROTTON, A. KILT: A modelling approach based on participatory agent-based simulation of styli- zed socio-ecosystems to stimulate social learning with local stakeholders. Springer Verlag, v. 10798 LNAI, p. 156–169, 2018.

TAILLANDIER, P. et al. Gama: A simulation platform that integrates geographical information data, agent-based modeling and multi-scale control. In: DESAI, N.; LIU, A.; WINI- KOFF, M. (Ed.). Principles and Practice of Multi-Agent Sys- tems. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. p. 242–258.

DROGOUL, A. et al. Gama: Multi-level and complex environment for agent-based models and simulations. In: Proceedings of the 2013 Int. Conf. on Aut. Agen. and Multi-agent Sys. Richland, SC: Int. Fou. for Aut. Agen. and Mult. Sys., 2013. (AAMAS ’13), p. 1361–1362.

TISUE, S.; WILENSKY, U. NetLogo: A simple environment for modeling complexity. Boston, MA, v. 21, p. 16–21, 01 2004.

NORTH, M. J.; COLLIER, N. T.; VOS, J. R. Experiences creating three implementations of the repast agent modeling toolkit. ACM Trans. Model. Comput. Simul., ACM, New York, NY, USA, v. 16, n. 1, p. 1–25, jan. 2006.

LUKE, S. et al. Mason: A multiagent simulation environment. Simulation, v. 81, n. 7, p. 517–527, 2005.

Nguyen Vu, Q. A. et al. Coherence and robustness in a disturbed mas. p. 1–4, July 2009.

TAILLANDIER, P.; BUARD, E. Designing agent behaviour in agent-based simulation through participatory method. In: YANG, J.-J. et al. (Ed.). Principles of Practice in Multi- Agent Systems. Berlin, Heidelberg: Springer Berlin Heidel- berg, 2009. p. 571–578.

CHU, T.-Q. et al. Interactive learning of independent experts’ criteria for rescue simulations. J. UCS, v. 15, p. 2701– 2725, 2009.

AMOUROUX, E. et al. GAMA: An environment for implementing and running spatially explicit multi-agent simulations. In: GHOSE, A.; GOVERNATORI, G.; SADANANDA, R. (Ed.). Agent Computing and Multi-Agent Systems. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. p. 359–371.


THEROND, O. et al. Integrated modelling of social-ecological systems: The MAELIA high-resolution multi- agent platform to deal with water scarcity problems. San Diego, California, United States, p. pp. 1, 2014.

AMOUROUX, E.; DESVAUX, S.; DROGOUL, A. Towards virtual epidemiology: An agent-based approach to the modeling of h5n1 propagation and persistence in north- vietnam. In: BUI, T. D.; HO, T. V.; HA, Q. T. (Ed.). Intelligent Agents and Multi-Agent Systems. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. p. 26–33. Water Resources Analysis: An Approach based on Agent-Based Modeling

YU, S.; HE, L.; LU, H. An environmental fairness based optimisation model for the decision-support of joint control over the water quantity and quality of a river basin. Journal of Hydrology, v. 535, 02 2016.




How to Cite

Farias, G., Leitzke, B., Born, M., Aguiar, M., & Adamatti, D. (2020). Water Resources Analysis: An Approach based on Agent-Based Modeling. Revista De Informática Teórica E Aplicada, 27(2), 81–95. https://doi.org/10.22456/2175-2745.94319



Selected Papers - WESAAC 2019