Developing multi-stakeholder forest management scenarios: A multi-agent system simulation approach applied in Indonesia

Forest Policy and Economics

Volumn 7, Issue 4, 2005, Pages 475-491

  Purnomo, Herry ^a,b   Mendoza, Guillermo A ^c   Prabhu, Ravi ^d   Yasmi, Yurdi ^b  

^a BOGOR AGRICULTURAL UNIVERSITY   (Indonesia)

^b CENTER FOR INTERNATIONAL FORESTRY RESEARCH   (Indonesia)

^c UNIVERSITY OF ILLINOIS AT URBANA CHAMPAIGN   (United States)

^d Center for International Forestry Research   (Zimbabwe)

Author keywords

Community managed resource; Multi agent systems; Multi stakeholder simulation; Participatory methods

Indexed keywords

COMMUMITY-MANAGED RESOURCES; MULTI-STAKEHOLDER MANAGEMENT SYSTEMS; STAKEHOLDERS;

COMPUTER SIMULATION; DECISION MAKING; MATHEMATICAL MODELS; MULTI AGENT SYSTEMS; STRATEGIC PLANNING;

FORESTRY;

DECISION MAKING; FORESTRY; MATHEMATICAL MODELS; SIMULATION; STRATEGIC ALLIANCES;

EID: 13444311047     PISSN: 13899341     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.forpol.2003.08.004     Document Type: Article

References (41)

1. Alder, D., Synnott, T.J., 1992. Permanent sample plot techniques for mixed tropical forests. University of Oxford Tropical Forestry Papers: 25
2. Antona, M., Bousquet, F., Le Page, C., Weber, J., Karsenty, A., Guizol P., 1998. Economic theory and renewable resource management. In: Sichman, J., Conte, R., Gilbert, N. (Eds.), MABS 1988. Lecture Notes in Artificial Intelligence 1534, 61-78
3. Axelrod R. The Complexity of Cooperation: Agent-based Models of Competition and Collaboration. 1997;Princeton University Press, New Jersey
4. Barreteau O., Bousquet F. SHADOC: a multi-agent model to tackle variability of irrigated systems. Annals of Operations Research. 94:2000;139-162
5. Barreteau O.F., Bousquet F., Attonaty J. Role-playing games for opening the black box of multi-agent systems: methods and lessons of its application to Senegal River valley irrigated systems. The Journal of Artificial Societies and Social Simulation. 4:(2):2002;. available from: www http://www.soc.surrey.ac.uk/ JASS/4/2/5.html (20 May 2001)
6. Bonnefoy J.-L., Le Page C., Rouchier J., Bousquet F. Modelling spatial practices and social representations of space using multi-agents. Ballot G., Weisbuch G. Application of Simulation to Social Science. 2000;155-168 Hermès, Paris
7. Bousquet, F., 1998. CORMAS: common pool resources and multi-agent systems. Lecture Notes in Computer System 14 (16), 826-838 (Springer)
8. Bousquet, F., Duthoit, Y., Proton, H., Lepage, C., Weber J., 1996. Tragedy of the commons, game theory and spatial simulation of complex systems. Proceedings Ecologie, Societie, Economie. Universite de Versailles-Saint Quentin en Yvelines, May 23-25
9. Bousquet F., Bakam I., Proton H., Le Page C. CORMAS: common-pool resources and multi-agent systems. Lecture Notes in Artificial Intelligence. 1416:1998;826-838
10. Bousquet F., Barretaeau O., Lepage C., Mullon C. An environmental modeling approach: the use of multi-agent simulations. Blasco F., Weill A. Advances in Environmental and Ecological Modelling. 1999;Elsevier, Paris
11. Bousquet F., Lepage C., Bakam I., Takforyan A. Multi-agent simulations of hunting wild meat in a village in eastern Cameroon. Ecological Modelling. 138:2001;331-346
12. Bousquet F., Barreteau O., d'Aquino P., et al. Multi-agent systems and role games: collective learning processes for ecosystem management. Janssen M. Complexity and Ecosystem Management: The Theory and Practice of Multi-agent Approaches. 2002;Edward Elgar Publishers
13. Castro A.P., Nielsen E. Indigenous people and co-management: implications for conflict management. J Environ Sci Pol. 4:2001;229-239
14. Colfer, C.J.P., Brocklesby, M.A., Diaw, C., et al., 1999. The BAG (Basic Assessment Guide for Human Well-Being). C&I Toolbox Series No. 5. CIFOR, Bogor, Indonesia
15. DeAngelis D.L., Gross L.J. Individual-based Models and Approaches in Ecology. 1992;Chapman and Hall
16. Drogul A., Ferber J. Multi-agent simulation as a tool for studying emergent societies. Gibert N., Doran J. Simulating Computer Simulation of Social Phenomena. 1994;UCL Press
17. Fahey L., Randall R.M. What is scenario learning? Fahey L., Randall R.M. Learning from the Future: Competitive Foresight Scenarios. 1998;3-21 Wiley, New York
18. Ferber J. Multi-agent Systems: An Introduction to Distributed Artificial Intelligence. 1999;Addison-Wesley, Reading, MA
19. Flores-Mendez, R.A., 1999. Towards a Standardization of Multi-Agent System Frameworks. ACM Crossroads Student Magazine. Available from: http://www.acm.org/crossroads/xrds5-4/multiagent.html. Accessed 13 September 2001
20. Grant J.W., Pedersen E.K., Marin S.L. Ecology and Natural Resource Management: System Analysis and Simulation. 1997;Addison-Wesley Publishing Company, Reading, MA
21. Grimm V. Ten years of individual based modeling in ecology: what have we learned and what could we learn in the future. Ecological Modelling. 115:1999;129-148
22. Hogeweg P., Hesper B. Individual-oriented modelling in ecology. Mathematical and Computer Modelling. 13:1990;83-90
23. Huston M., DeAngelis D., et al. New computer models unify ecological theory. Bioscience. 38:1988;682-691
24. Ossowski S. Co-ordination in Artificial Agent Societies: Social Structures and its Implications for Autonomous Problem Solving Agents. 1999;Springer, Berlin
25. Painch M., Hinton R. Simulation models: a tool for rigorous scenario analysis. Fahey L., Randall R.M. Learning from the Future: Competitive Foresight Scenarios. 1998;157-174 John Wiley & Sons, Inc, New York
26. Peluso N.L., Vandergeest P., Potter L. Social aspects of forestry in Southeast Asia: a review of the trends in the scholarly literature. Journal of Southeast Asian Studies. 26:(1):1995;196-218
27. Purnomo, H., 2002. A modeling approach to collaborative forest management. Ph.D. dissertation. Bogor Agricultural University
28. Richards M., Davies J., Yaron G. Stakeholder Incentives in Participatory Forest Management. 2003;Overseas Development Institute (ODI), UK
29. Rosner B. Fundamentals of Biostatistics. fourth ed.:1995;Duxbury Press, Belmont, CA
30. Rouchier, J., Bousquet, F., Barreteau, O., Le Page, C., Bonnefoy, J.-L., 2000. Multi-agent modelling and renewable resources issues: the relevance of shared representations for interacting agents. In: Moss, S., Davidsson, P. (Eds.), MABS 2000. Lecture Notes in Artificial Intelligence 1979, 181-197
31. Rouchier J., Bousquet F., Requier-Dejardins M., Antona M. A multi-agent model for transhumance in North Cameroon. Journal of Economic Dynamics and Control. 25:2001;527-559
32. Sarin, M., 2001. Disempowerment in the name of 'participatory' forestry? - Village joint forest management project in Uttarakhand. Forest Tree and People No 44
33. Saxena K.G., Rao K.S., Sen K.K., Maikhuri R.K., Semwal R.L. Integrated natural resource management: approaches and lessons from the Himalaya. Conservation Ecology. 5:(2):2002;. http://www.consecol.org/vol 5/iss 2/art 14/index.html
34. Septiana, A.R., 2000. Simulasi Pengaturan Hasil Hutan. Diploma Thesis. Bogor Agricultural University
35. Sist, P., Kartawinata, K., Priyadi, H., Sheil, D., 2003. Comparison of logging impacts with conventional and Reduced-impact logging techniques in mixed dipterocarp forest of North-East Borneo, CIFOR special report.
36. Sokal R.R., Rohlf F.J. Biometry. third ed.:1995;W.H. Freeman and Co, New York
37. Stone, P., Veloso, M., 1997. Multiagent Systems: A Survey from a Machine Learning Perspective. Computer Science Department, Carnegie Mellon University, Pittsburgh, PA 15213. Available from: http://www-2.cs.cmu.edu/afs/cs/usr/pstone/ public/papers/97MAS-survey/revised-survey.html [20 October 2001]
38. Sukwong, S., 2000. Linking local lessons to policy development. Paper presented at the Fourth International Workshop on Model Forests for Filed Level Applications of SFM, Japan, 23-27 October 2000.
39. Sycara, K., 2000. Multi-agent systems (a subtopic of agents), American Association for Artificial Intelligence (AAAI). Available from: http://www.aaai.org/AITopics/html/multi.html. Accessed 19 September 2001.
40. Thebaud O., Locatelli B. Modeling the emergence of resource sharing conventions: an agent-based approach. The Journal of Artificial Societies and Social Simulation. 4:(2):2001;. available from: http://www.soc.surrey.ac.uk/ JASS/4/2/3.html
41. Weiss G. Multi Agent Systems: A Modern Approach to Distributed Artificial Intelligence. 1999;MIT Press, Cambridge, MA