Motivation

AI for Conservation refers to the application of artificial intelligence to conservation, such as wildlife protection and the protection of natural resources. For example, in the green security domain, the repeated and strategic interaction between those who protect these resources and those who seek to attack or exploit these resources can be modeled using game theory as a repeated game. While our predictive analytics effort focuses on predicting where adversaries (e.g., poachers) will strike, our prescriptive analytics work provides recommendations to defenders (e.g., rangers) to conduct strategic, randomized patrols. These analytics can be supported using machine learning, for example by detecting poachers or animals in unmanned aerial vehicle (UAV) imagery automatically.

Milind Tambe

Debarun Kar

Benjamin Ford

Shahrzad Gholami

Fei Fang

Thanh Hong Nguyen

Rong Yang

Francesco Maria Delle Fave

Rob Pickles, Panthera

Wai Y. Lam Gopalasamy R. Clements, Panthera & Rimba

Andrew Lemieux, Nethelands Institute for the Study of Crime and Law Enforcement

Andrew J, Plumptre, Wildlife Conservation Society

Lucas Joppa, Microsoft Research

Arnaud Lyet, World Wildlife Fund

Nicole Sintov, Sol Price School of Public Policy, USC

Bo An, Nanyang Technological University

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