@conference {1504602,
	title = {Patrol Strategies to Maximize Pristine Forest Area },
	booktitle = {Conference on Artificial Intelligence (AAAI)	},
	year = {2012},
	abstract = {Illegal extraction of forest resources is fought, in many developing countries, by patrols that try to make this activity
less profitable, using the threat of confiscation. With a limited
budget, officials will try to distribute the patrols throughout
the forest intelligently, in order to most effectively limit extraction. Prior work in forest economics has formalized this
as a Stackelberg game, one very different in character from
the discrete Stackelberg problem settings previously studied
in the multiagent literature. Specifically, the leader wishes to
minimize the distance by which a profit-maximizing extractor will trespass into the forest{\textemdash}or to maximize the radius
of the remaining {\textquotedblleft}pristine{\textquotedblright} forest area. The follower{\textquoteright}s costbenefit analysis of potential trespass distances is affected by
the likelihood of being caught and suffering confiscation.
In this paper, we give a near-optimal patrol allocation algorithm and a 1/2-approximation algorithm, the latter of which
is more efficient and yields simpler, more practical patrol allocations. Our simulations indicate that these algorithms substantially outperform existing heuristic allocations.},
	author = {Matthew P. Johnson and Fang, Fei and Tambe, Milind}
}
