| Summary: | Wildland fires (or wildfires) occur on all continents ex-cept for Antarctica. These fires threaten communities, change ecosystems, destroy vast quantities of natural re-sources and the cost estimates of the damage done an-nually is in the billions of dollars. Controlling wildland fires is resource-intensive and there are numerous ex-amples where the resource demand has outstripped re-source availability. Trends in changing climates, fire oc-currence and the expansion of the wildland-urban inter-face all point to increased resource shortages in the fu-ture. One approach for coping with these shortages has been the sharing of resources across different wildland-fire agencies. This introduces new issues as agencies have to balance their own needs and risk-management with their desire to help fellow agencies in need. Using ideas from the field of multiagent systems, we conduct the first analysis of strategic issues arising in resource-sharing for wildland-fire control. We also argue that the wildland-fire domain has numerous features that make it attractive to researchers in artificial intelligence and computational sustainability.
|
|---|