This article presents PAWS, a game-theoretic application deployed in Southeast Asia for optimizing foot patrols to combat poaching. In this article, we report on the
significant evolution of PAWS from a proposed decision aid
introduced in 2014 to a regularly deployed application. We
outline key technical advances that lead to PAWS’s regular
deployment: ( 1) incorporating complex topographic features, for example, ridgelines, in generating patrol routes; ( 2)
handling uncertainties in species distribution (
game-theoretic payoffs); ( 3) ensuring scalability for patrolling large-scale
conservation areas with fine-grained guidance; and ( 4) handling complex patrol scheduling constraints.
Poaching is a serious threat to wildlife conservation and
can lead to the extinction of species and destruction of
ecosystems. For example, poaching is considered a major
driver (Chapron et al. 2008) of why tigers are now found in
less than 7 percent of their historical range (Sanderson et al.
2006), with three out of nine tiger subspecies already extinct
(IUCN 2015). As a result, efforts have been made by law
enforcement agencies in many countries to protect endangered animals from poaching. The most direct and commonly used approach is conducting foot patrols. However,
given their limited human resources and the vast area in
need of protection, improving the efficiency of patrols
remains a major challenge.
PAWS — A Deployed
Game-Theoretic Application
to Combat Poaching
Fei Fang, Thanh H. Nguyen, Robert Pickles, Wai Y. Lam, Gopalasamy R. Clements,
Bo An, Amandeep Singh, Brian C. Schwedock, Milind Tambe, Andrew Lemieux
n Poaching is considered a major
driver for the population drop of
key species such as tigers, elephants, and rhinos, which can be
detrimental to whole ecosystems.
While conducting foot patrols is
the most commonly used
approach in many countries to
prevent poaching, such patrols
often do not make the best use of
the limited patrolling resources.
