TY - GEN
T1 - Protecting the NECTAR of the Ganga River through game-theoretic factory inspections
AU - Ford, Benjamin
AU - Brown, Matthew
AU - Yadav, Amulya
AU - Singh, Amandeep
AU - Sinha, Arunesh
AU - Srivastava, Biplav
AU - Kiekintveld, Christopher
AU - Tambe, Milind
N1 - Publisher Copyright:
© Springer International Publishing Switzerland 2016.
PY - 2016
Y1 - 2016
N2 - Leather is an integral part of the world economy and a substantial income source for developing countries. Despite government regulations on leather tannery waste emissions, inspection agencies lack adequate enforcement resources, and tanneries’ toxic wastewaters wreak havoc on surrounding ecosystems and communities. Previous works in this domain stop short of generating executable solutions for inspection agencies. We introduce NECTAR-the first security game application to generate environmental compliance inspection schedules. NECTAR’s game model addresses many important real-world constraints: a lack of defender resources is alleviated via a secondary inspection type; imperfect inspections are modeled via a heterogeneous failure rate; and uncertainty, in traveling through a road network and in conducting inspections, is addressed via a Markov Decision Process. To evaluate our model, we conduct a series of simulations and analyze their policy implications.
AB - Leather is an integral part of the world economy and a substantial income source for developing countries. Despite government regulations on leather tannery waste emissions, inspection agencies lack adequate enforcement resources, and tanneries’ toxic wastewaters wreak havoc on surrounding ecosystems and communities. Previous works in this domain stop short of generating executable solutions for inspection agencies. We introduce NECTAR-the first security game application to generate environmental compliance inspection schedules. NECTAR’s game model addresses many important real-world constraints: a lack of defender resources is alleviated via a secondary inspection type; imperfect inspections are modeled via a heterogeneous failure rate; and uncertainty, in traveling through a road network and in conducting inspections, is addressed via a Markov Decision Process. To evaluate our model, we conduct a series of simulations and analyze their policy implications.
UR - http://www.scopus.com/inward/record.url?scp=84977535464&partnerID=8YFLogxK
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U2 - 10.1007/978-3-319-39324-7_9
DO - 10.1007/978-3-319-39324-7_9
M3 - Conference contribution
AN - SCOPUS:84977535464
SN - 9783319393230
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 97
EP - 108
BT - Advances in Practical Applications of Scalable Multi-agent Systems
A2 - Ito, Takayuki
A2 - Escalona, Maria José
A2 - Demazeau, Yves
A2 - Bajo, Javier
PB - Springer Verlag
T2 - 14th International Conference on Advances in Practical Applications of Scalable Multi-agent Systems, PAAMS 2016
Y2 - 1 June 2016 through 3 June 2016
ER -