'The book Artificial Intelligence and Conservation brings together, for the first time, examples of computational research that address problems in conservation. The contributors articulate the challenges of using artificial intelligence to solve biodiversity conservation problems, as well as the urgency of the necessity to do so. It is a sweeping exposition, ranging from using game theory to fight poaching, to optimizing decisions through Markov modeling to manage invasive species. The collection showcases how rigorous computational research can make an impact helping save our planet's wildlife. The readers will not only discover interesting computational problems and solutions, but will be inspired to work in this unique application of artificial intelligence and, I hope, will solve the many pressing open problems posed by the authors.' Tanya Berger-Wolf, University of Illinois, Chicago
Part I: 1. Introduction Fei Fang, Milind Tambe, Bistra Dilkina and Andrew J. Plumptre; Part II: 2. Law enforcement for wildlife conservation Andrew J. Plumptre; 3. Wildlife poaching forecasting based on ranger-collected data and evaluation through field tests Shahrzad Gholami, Benjamin Ford, Debarun Kar, Fei Fang, Andrew J. Plumptre, Milind Tambe, Margaret Driciru, Fred Wanyama, Aggrey Rwetsiba, Mustafa Nsubuga and Joshua Mabonga; 4. Optimal patrol planning against black-box attackers Haifeng Xu, Benjamin Ford, Fei Fang, Bistra Dilkina, Andrew J. Plumptre, Milind Tambe, Margaret Driciru, Fred Wanyama, Aggrey Rwetsiba, Mustafa Nsubuga and Joshua Mabonga; 5. Automatic detection of poachers and wildlife with UAVs Elizabeth Bondi, Fei Fang, Mark Hamilton, Debarun Kar, Donnabell Dmello, Venil Noronha, Jongmoo Choi, Robert Hannaford, Arvind Iyer, Lucas Joppa, Milind Tambe and Ram Nevatia; Part III: 6. Protecting coral reef ecosystems via efficient patrols Yue Yin and Bo An; 7. Simultaneous optimization of strategic and tactical planning for environmental sustainability and security Sara M. McCarthy, Milind Tambe, Christopher Kiekintveld, Meredith L. Gore and Alex Killion; 8. NECTAR Benjamin Ford, Matthew Brown, Amulya Yadav, Amandeep Singh, Arunesh Sinha, Biplav Srivastava, Christopher Kiekintveld and Milind Tambe; 9. Connecting conservation research and implementation Sean McGregor, Rachel M. Houtman, Ronald Metoyer and Thomas G. Dietterich; 10. Probabilistic inference with generating functions for animal populations Daniel Sheldon, Kevin Winner and Debora Sujono; 11. Engaging citizen scientists in data collection for conservation Yexiang Xue and Carla P. Gomes; 12. Simulator-defined Markov decision processes H. Jo Albers, Thomas G. Dietterich, Kim Hall, Majid A. Taleghan and Katherine Lee.