Designing Patrol Strategies to Maximize Pristine Forest Area


Matthew P Johnson, Fei Fang, Milind Tambe, and H. J. Albers. 2012. “Designing Patrol Strategies to Maximize Pristine Forest Area .” In Workshop on Optimization in Multiagent Systems (OPTMAS) at AAMAS .


Illegal extraction of forest resources is fought, in many developing countries, by patrols that seek to deter such activity by decreasing its profitability. With a limited budget, a patrol strategy will seek to distribute the patrols throughout the forest, in order to minimize the resulting amount of extraction that occurs or maximize the amount of “pristine” forest area. Prior work in forest economics has posed this problem as a Stackelberg game, but efficient optimal or approximation algorithms for generating leader strategies have not previously been found. Unlike previous work on Stackelberg games in the multiagent literature, much of it motivated by counter-terrorism, here we seek to protect a continuous area, as much as possible, from extraction by an indeterminate number of followers. The continuous nature of this problem setting leads to new challenges and solutions, very different in character from in the discrete Stackelberg settings previously studied. In this paper, we give an optimal patrol allocation algorithm and a guaranteed approximation algorithm, the latter of which is more efficient and yields simpler, more practical patrol allocations. In our experimental investigations, we find that these algorithms perform significantly better—yielding a larger pristine area—than naive patrol allocations.
See also: 2012