MASE-BDI: Agents with Practical Reasoning for Land Use and Cover Change Simulation
Resumo
Agents with a cognitive dimension are paramount to represent and understand land use and land cover changes that involves decision making. A Belief-Desire-Intention(BDI)-Agent system for environmental simulation was developed:the MASE-BDI framework. MASE-BDI, a novel version of MASE, implements agents that can be represented by their individual beliefs and in- tentional behavior to choose plans of action in a complex environment. We investigate the advantages, limitations and drawbacks of this new design and how practical reasoning agents can contribute to decision support for sustain- ability. Experiments were made in a spatially explicit LUCC study case of the Brazilian Cerrado between the years of 2002 and 2008. MASE-BDI simulation results were compared to those obtained with the multi-agent system for land- use change simulation previously developed in this research project.
Referências
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Grimm, V., Berger, U., Bastiansen, F., Eliassen, S., Ginot, V., Giske, J., Goss-Custard, J., Grand, T., Heinz, S. K., and Huse, G. (2006). A standard protocol for describing individual-based and agent-based models. Ecological Modelling, 198(1-2):115–126.
Kangas, J. and Kangas, A. (2005). Multiple criteria decision support in forest management - the approach, methods applied, and experiences gained. Forest Ecology and Management, 207(1–2):133–143.
Le, Q. B., Park, S. J., Vlek, P. L., and Zambonelli, F. (2008). Land-use dynamic simulator(LUDAS): A multi-agent system model for simulating spatio-temporal dynamics of coupled human landscape system. Structure and theoretical specification. Ecological Informatics, 3(2):135–153.
Matthews, R. B., Gilbert, N. G., Roach, A., Polhill, J. G., and Gotts, N. M. (2007). Agentbased land-use models : a review of applications. Landscape Ecology, pages 1447–1459.
Paegelow, M., Camacho Olmedo, M. T., Mas, J.-F., and Houet, T. (2014). Benchmarking of LUCC modelling tools by various validation techniques and error analysis. Cybergeo, 701(online):29.
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Pontius, RobertGilmore, J., Boersma, W., Castella, J.-C., Clarke, K., Nijs, T., Dietzel, C., Duan, Z., Fotsing, E., Goldstein, N., Kok, K., Koomen, E., Lippitt, C., McConnell,W., Mohd Sood, A., Pijanowski, B., Pithadia, S., Sweeney, S., Trung, T., Veldkamp, A., and Verburg, P. (2008). Comparing the input, output, and validation maps for several models of land change. The Annals of Regional Science, 42(1):11–37.
Railsback, S. F., Lytinen, S. L., and Jackson, S. K. (2006). Agent-based simulation platforms: Review and development recommendations. SIMULATION, 82(9):609–623.
Ralha, C. G., Abreu, C. G., Coelho, C. G. C., Zaghetto, A., Macchiavello, B., and Machado, R. B. (2013a). A multi-agent model system for land-use change simulation. Environmental Modelling & Software, 42(0):30 – 46.
Ralha, C. G., Abreu, C. G., and Coelho, C. G. D. C. (2013b). Mase : Multi-agent system for environmental simulation. In IV Workshop de Computação Aplicada à Gest˜ao do Meio Ambiente e Recursos Naturais, pages 1–5, Maceio-AL. SBC.
Sano, E. E., Rosa, R., Brito, J. L. S., and Ferreira, L. G. (2008). Mapeamento semidetalhado do uso da terra do bioma cerrado. Pesquisa Agropecuaria Brasileira, 43(1):153– 156.
Smajgl, A., Brown, D. G., Valbuena, D., and Huigen, M. G. A. (2011). Empirical characterisation of agent behaviours in socio-ecological systems. Enviromental Modelling & Software, 26(7):837–844.
Turner II, B. L. (2002). Toward integrated land-change science advances in 1.5 decades of sustained international research. In Steffan, W., Jager, J., Carson, D., and Bradshaw, C., editors, Challenges of a Changing Earth: Proceedings of the Global Change Open Science Conference, Amsterdam, NL, 10-13 July 2000, pages 269–272. Springer Verlag.
Verburg, P. H. (2006). Simulating feedbacks in land use and land cover change models. Landscape Ecology, 21(8):1171–1183.
Bousquet, F. and Le Page, C. (2004). Multi-agent simulations and ecosystem management : a review. Ecological Modelling, 176:313–332.
Bratman, M. (1987). Intention, Plans, and Practical Reason. Harvard University Press, Cambridge, Massachusetts.
Dennett, D. C. (1989). The Intentional Stance. A Bradford book. MIT Press, Cambridge, Massachusetts.
Elliot, S. (2011). Transdisciplinary perspectives on environmental sustainability: A resource base and framework for it-enabled business transformation. Management Information Systems Quarterly, 35(1):197–236.
Grimm, V., Berger, U., Bastiansen, F., Eliassen, S., Ginot, V., Giske, J., Goss-Custard, J., Grand, T., Heinz, S. K., and Huse, G. (2006). A standard protocol for describing individual-based and agent-based models. Ecological Modelling, 198(1-2):115–126.
Kangas, J. and Kangas, A. (2005). Multiple criteria decision support in forest management - the approach, methods applied, and experiences gained. Forest Ecology and Management, 207(1–2):133–143.
Le, Q. B., Park, S. J., Vlek, P. L., and Zambonelli, F. (2008). Land-use dynamic simulator(LUDAS): A multi-agent system model for simulating spatio-temporal dynamics of coupled human landscape system. Structure and theoretical specification. Ecological Informatics, 3(2):135–153.
Matthews, R. B., Gilbert, N. G., Roach, A., Polhill, J. G., and Gotts, N. M. (2007). Agentbased land-use models : a review of applications. Landscape Ecology, pages 1447–1459.
Paegelow, M., Camacho Olmedo, M. T., Mas, J.-F., and Houet, T. (2014). Benchmarking of LUCC modelling tools by various validation techniques and error analysis. Cybergeo, 701(online):29.
Pokahr, A., Braubach, L., and Lamersdorf, W. (2003). Jadex: Implementing a BDIInfrastructure for JADE Agents. EXP, 3(3):76–85.
Pontius, RobertGilmore, J., Boersma, W., Castella, J.-C., Clarke, K., Nijs, T., Dietzel, C., Duan, Z., Fotsing, E., Goldstein, N., Kok, K., Koomen, E., Lippitt, C., McConnell,W., Mohd Sood, A., Pijanowski, B., Pithadia, S., Sweeney, S., Trung, T., Veldkamp, A., and Verburg, P. (2008). Comparing the input, output, and validation maps for several models of land change. The Annals of Regional Science, 42(1):11–37.
Railsback, S. F., Lytinen, S. L., and Jackson, S. K. (2006). Agent-based simulation platforms: Review and development recommendations. SIMULATION, 82(9):609–623.
Ralha, C. G., Abreu, C. G., Coelho, C. G. C., Zaghetto, A., Macchiavello, B., and Machado, R. B. (2013a). A multi-agent model system for land-use change simulation. Environmental Modelling & Software, 42(0):30 – 46.
Ralha, C. G., Abreu, C. G., and Coelho, C. G. D. C. (2013b). Mase : Multi-agent system for environmental simulation. In IV Workshop de Computação Aplicada à Gest˜ao do Meio Ambiente e Recursos Naturais, pages 1–5, Maceio-AL. SBC.
Sano, E. E., Rosa, R., Brito, J. L. S., and Ferreira, L. G. (2008). Mapeamento semidetalhado do uso da terra do bioma cerrado. Pesquisa Agropecuaria Brasileira, 43(1):153– 156.
Smajgl, A., Brown, D. G., Valbuena, D., and Huigen, M. G. A. (2011). Empirical characterisation of agent behaviours in socio-ecological systems. Enviromental Modelling & Software, 26(7):837–844.
Turner II, B. L. (2002). Toward integrated land-change science advances in 1.5 decades of sustained international research. In Steffan, W., Jager, J., Carson, D., and Bradshaw, C., editors, Challenges of a Changing Earth: Proceedings of the Global Change Open Science Conference, Amsterdam, NL, 10-13 July 2000, pages 269–272. Springer Verlag.
Verburg, P. H. (2006). Simulating feedbacks in land use and land cover change models. Landscape Ecology, 21(8):1171–1183.
Publicado
20/07/2015
Como Citar
ABREU, Carolina; COELHO, Cássio; RALHA, Célia.
MASE-BDI: Agents with Practical Reasoning for Land Use and Cover Change Simulation. In: WORKSHOP DE COMPUTAÇÃO APLICADA À GESTÃO DO MEIO AMBIENTE E RECURSOS NATURAIS (WCAMA), 6. , 2015, Recife.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2015
.
p. 65-74.
ISSN 2595-6124.
DOI: https://doi.org/10.5753/wcama.2015.10191.
