Fostering industrial symbiosis with agent-based simulation and participatory modeling

Journal of Industrial Ecology

Volumn 13, Issue 2, 2009, Pages 197-213

  Batten, David F ^a  

^a CSIRO   (Australia)

Author keywords

Coevolutionary learning; Companion modeling; Complex systems science; Complexity; Eco efficiency; Industrial ecology (IE)

Indexed keywords

COEVOLUTIONARY LEARNING; COMPANION MODELING; COMPLEX SYSTEMS SCIENCE; COMPLEXITY; ECO-EFFICIENCY; INDUSTRIAL ECOLOGY (IE);

ECOSYSTEMS; EDUCATION; EFFICIENCY; LARGE SCALE SYSTEMS; RENEWABLE ENERGY RESOURCES;

INDUSTRY;

ECOLOGICAL ECONOMICS; LEARNING; MODELING; PARTICIPATORY APPROACH;

EID: 67049155400     PISSN: 10881980     EISSN: 15309290     Source Type: Journal    
DOI: 10.1111/j.1530-9290.2009.00115.x     Document Type: Article

References (36)

1. Ackermann, T., G. Andersson, and L. Söder. 2001. Distributed generation: A definition. Electric Power Systems Research 57(3): 195-204.
2. Andrews, C. J. 2001. Does electricity deregulation promote eco-efficiency: The case of distributed generation. Paper presented at the American Collegiate Schools of Planning Annual Conference, 8-11 November, Cleveland, Ohio.
3. Axelrod, R. 1997. The complexity of cooperation: Agentbased models of competition and cooperation. Princeton, NJ: Princeton University Press.
4. Axtell, R., C. Andrews, and M.J. Small. 2001. Agent-based modeling and industrial ecology. Journal of Industrial Ecology 5(4): 10-13.
5. Barreteau, O. 2003. The joint use of role-playing games and models regarding negotiation processes: Characterization of associations. Journal of Artificial Societies and Social Simulation 6(2). http://jasss.soc.surrey. ac.uk/6/2/3.html. Accessed February 2009.
6. Batten, D. F. 1982. On the dynamics of industrial evolution. Regional Science and Urban Economics 12(3): 449-462.
7. Batten, D. F. 2000. Discovering artificial economics: How agents learn and economies evolve. New York: Westview Press.
8. Batten, D. F. and S. Cook. 2008. Industrial symbiosis for Dandenong LOGIS: Final report, prepared for VicUrban Melbourne: Temaplan - CSIRO - VicUrban.
9. Batten, D. F. and G. Grozev. 2006. NEMSIM: Finding ways to reduce greenhouse gases using multi-agent electricity modeling. In Complex science for a complex world: Human ecosystems modeling with agents, edited by P. Pascal and D. Batten. Canberra, Australia: ANU ePress.
10. Batten, D. F. and G. Grozev. 2008. Managing energy futures and greenhouse gas emissions with the help of agent-based simulation. In Changing stocks, flows and behaviors in industrial ecosystems, edited by M. Ruth and B. Davidsdottir. Cheltenham, Edward Elgar.
11. Bousquet, F., I. Bakam, H. Proton, and C. Le Page. 1998. CORMAS: Common-pool resources and multi-agent systems. Lecture Notes in Artificial Intelligence 1416: 826-838.
12. Bousquet, F., G. Tŕ ebuil and B. Hardy, eds. 2005. Companion modeling and multi-agent systems for integrated natural resource management in Asia. Los Banos, Philippines: IRRI Press.
13. Bower, J. and D. W. Bunn. 2000. A model-based comparison of pool and bilateral market mechanisms for electricity trading. Energy Journal 21(3): 1-29.
14. Bunn, D. W. and F. S. Oliveira. 2001. Agent-based simulation: An application to new electricity trading arrangements of England and Wales. IEEE Transactions on Evolutionary Computation 5(5): 493-503.
15. Bunn, D. W. and F. S. Oliveira. 2003. Evaluating individual market power in electricity markets via agent-based simulation. Annals of Operations Research 121: 57-77.
16. Ehrenfeld, J. and N. Gertler. 1997. Industrial ecology in practice: The evolution of interdependence at Kalundborg. Journal of Industrial Ecology 1(1): 67-79.
17. Epstein, J. M. and R. Axtell. 1996. Growing artificial societies: Social science from the bottomup. Washington, DC: Brookings Institution Press.
18. Frosch, R. A. and N. E. Gallopoulos. 1989. Strategies for manufacturing. Scientific American 266: 144-152.
19. Gardner, M. 1970. The fantastic combinations of John Conway's new solitaire game "life." Scientific American 223: 120-123.
20. Gilbert, N. and K. G. Troitzsch. 1999. Simulation for the social scientist. Buckingham, UK: Open University Press.
21. Gurung, T., F. Bousquet, and G. Tŕ ebuil. 2006. Companion modeling, conflict resolution and institution building: Sharing irrigation water in the Lingmuteychu watershed, Bhutan. Ecology and Society 11(2): 36-58.
22. Haken, H. 1983. Advanced synergetics. Berlin: Springer-Verlag.
23. Hoff, T., H. Wenger, and B. Farmer. 1996. Distributed generation: An alternative to electric utility investment in system capacity. Energy Policy 24(2): 137-147.
24. Hu, X., G. Grozev, and D. Batten. 2005. Empirical observations of bidding patterns in Australia's national electricity market. Energy Policy 33(16): 2075-2086.
25. Janssen, M. and E. Ostrom. 2006. Governing socialecological systems. In Handbook of computational economics: Volume 2. Agent-based computational economics, edited by L. Tesfatsion and K. L. Judd. Amsterdam: North-Holland.
26. Langton, C. 1995. Artificial life: An overview. Cambridge, MA: MIT Press.
27. Lowe, E. A. and L. K. Evans. 1995. Industrial ecology and industrial ecosystems. Journal of Cleaner Production 3(1-2): 47-53.
28. Nicolaisen, J., V. Petrov, and L. Tesfatsion. 2001. Market power and efficiency in a computational electricity market with discriminatory double auction pricing. Economic Report No. 52. Ames: Iowa State University.
29. Nicolis, G. and I. Prigogine. 1977. Self-organization in non-equilibrium systems. New York: Wiley-Interscience.
30. Pepermans, G., J. Driesen, D. Haeseldonckx, R. Belmans, and W. D'Haeseleer. 2005. Distributed generation: Definition, benefits and issues. Energy Policy 33(6): 787-798.
31. Perez, P. and D. Batten, eds. 2006. Complex science for a complex world: Exploring human ecosystems with agents. Canberra, Australia: ANU ePress.
32. Resnick, M. 1999. Turtles, termites and traffic jams: Explorations in massively parallel microworlds. Cambridge, MA: MIT Press.
33. Roth, A. E. and I. Erev. 1995. Learning in extensive form games: Experimental data and simple dynamic models in the intermediate term. Games and Economic Behavior 8: 164-212.
34. Tesfatsion, L. and K. L. Judd, eds. 2006. Handbook of computational economics: Volume 2. Agent-based computational economics. Amsterdam: North-Holland.
35. Veselka, T., G. Boyd, G. Conzelmann, V. Koritarov, C. Macal, M. North, B. Schoepfle, and P. Thimmapuram. 2002. Simulating the behavior of electricity markets with an agent-based methodology: The EMCAS model. Paper presented at the International Association for Energy Economists North American Conference, 6-8 October, Vancouver, British Columbia, Canada.
36. Wallner, H. P. 1999. Towards sustainable development of industry: Networking, complexity and eco-clusters. Journal of Cleaner Production 7: 49-58.