Wildfire disasters threaten numerous communities and ecosystems in America today. An effective policy strategy to counteract the threat of wildfire disasters would entail the reduction of accumulated fuels (flammable organic materials) found across large areas in many American ecosystems. Major uncertainties surround this policy endeavor because fuel reduction has never been attempted on such large scales before. This study outlines an adaptive policy strategy designed to resolve these uncertainties through a systematic process of learning. An adaptive wildfire policy would employ fuel reduction experiments on large scales, with the goal of generating new knowledge to progressively improve the effectiveness of fuel reduction strategies over time.