Complexity and Ecosystem Management: The Theory and Practice of Multi-agent SystemsMarco Janssen Edward Elgar Publishing, 1 janv. 2002 - 344 pages The quality of ecosystems is affected by the actions of different stakeholders who use them in a variety of ways. In order to understand this complex relationship between humans and nature, it is vital to understand the complexity of the interacting agent |
Table des matières
| 1 | |
Methods and Concepts | 11 |
The transition from local to global dynamics a proposed framework for agentbased thinking in social ecological systems | 13 |
Changing the rules of the game lessons from immunology and linguistics for selforganization of institutions | 35 |
Futures predictions and other foolishness | 48 |
Validation and verification of multi agent systems | 63 |
Using artificial agents to understand laboratory experiments of commonpool resources with real agents | 75 |
Implications of spatial heterogeneity of grazing pressure on the resilience of rangelands | 103 |
Adjustment costs of agrienvironmental policy switchings an agentbased analysis of the German region Hohenlohe | 127 |
Agentbased simulation of organic farming conversion in Allier département | 158 |
Scientific measurements and villagers knowledge an integrative multiagent model from the semiarid areas of Zimbabwe | 188 |
Simulating landcover change in SouthCentral Indiana an agentbased model of deforestation and afforestation | 218 |
Multiagent systems and role games collective learning processes for ecosystem management | 248 |
Institutional change for sustainable land use a participatory approach from Australia | 286 |
| 314 | |
| 343 | |
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Expressions et termes fréquents
Agenda agent-based model agents aggregated agricultural agro-ecosystem Allier analysis approach average behavior biomass cells chapter cognitive common-pool resource complex adaptive systems consumat costs cotton crop decision developed discussion dynamics ecological economic land rent ecosystem management effect emergent empirical environment evaluation evolution example experiments exploration factor fallow farmers Figure forest framework function game theory grass heterogeneity Homo economicus households immune system impact increase Indiana individual initial institutions interactions investment labor land-cover change land-use landscape livestock density maize Masoka mean multi-agent models multi-agent system models multi-agent systems Nash Nash equilibrium observed organic farming Ostrom outcomes paddock parameters patterns players population pre-Agenda prediction problems production rainfall rangeland region rental prices represent resilience risk aversion role game rules scenarios sheep simulation slope social-ecological systems sorghum spatial specific stakeholders strategy structure tokens types understanding utility validation values variables yields
Fréquemment cités
Page 317 - Bian, L. (1997) Multiscale nature of spatial data in scaling up environmental models, in DA Quattrochi and MF Goodchild (eds) Scale in Remote Sensing and GIS, Raton Lewis Publishers, Boca Raton, FL, 13-26.
Page 327 - WD and CW Ramm, 1987. Correct Formulation of the Kappa Coefficient of Agreement.