PAWS: adaptive game-theoretic patrolling for wildlife protection

نویسندگان

  • Benjamin J. Ford
  • Debarun Kar
  • Francesco Maria Delle Fave
  • Rong Yang
  • Milind Tambe
چکیده

Endangered species around the world are in danger of extinction from poaching. From the start of the 20th century, the African rhino population has dropped over 98% [4] and the global tiger population has dropped over 95% [5], resulting in multiple species extinctions in both groups. Species extinctions have negative consequences on local ecosystems, economies, and communities. To protect these species, countries have set up conservation agencies and national parks, such as Uganda’s Queen Elizabeth National Park (QENP). However, a common lack of funding for these agencies results in a lack of law enforcement resources to protect these large, rural areas. As an example of the scale of disparity, one wildlife crime study in 2007 reported an actual coverage density of one ranger per 167 square kilometers [2]. Because of the hazards involved (e.g., armed poachers, wild animals), rangers patrol in groups, further increasing the amount of area they are responsible for patrolling. Security game research has typically been concerned with combating terrorism, and this field has indeed benefited from a range of successfully deployed applications [1, 6]. These applications have enabled security agencies to make more efficient use of their limited resources. In this previous research, adversary data has been absent during the development of these solutions, and thus, it has been difficult to make accurate adversary behavior models during algorithm development. In a domain such as wildlife crime, interactions with the adversary are frequent and repeated, thus enabling conservation agencies to collect data. This presence of data enables security game researchers to begin developing algorithms that incorporate this data into, potentially, more accurate behavior models and consequently better security solutions. Developed in conjunction with staff at QENP, the Protection Assistant for Wildlife Security (PAWS) generates optimized defender strategies for use by park rangers [7]. Due to the repeated nature of wildlife crime, PAWS is able to lever-

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تاریخ انتشار 2014