AI for Conservation
Game Theory and Machine Learning to Combat Crimes Against the Environment
MOTIVATION
FEATURES
VIDEOS
Overview of AI for Conservation
2022 KDD Keynote by Milind Tambe
PAWS: AI to Predict Poaching and Illegal Logging
2021 AI for Climate talk by Lily Xu
Poachers Have Killed All the Tigers in this Cambodian Wildlife Sanctuary but Rangers Are Fighting Back with Artificial Intelligence
Poachers have killed all the tigers in this Cambodian wildlife sanctuary but rangers are fighting back with artificial intelligence pic.twitter.com/QkEo5pVRUR
— BBC World Service (@bbcworldservice) August 14, 2019
How is AI being used to protect the world’s most endangered animals?
Using Ranger-Generated Data for Predictive Patrol Planning - Evidence to Action #Research4IWT18
Green Security: How can AI help in protecting Forests, Fish and Wildlife
Green Security Game refers to the general framework to model the repeated and strategic interaction in green security domains such as wildlife protection and fishery protection. In Green Security Game framework, the problem in these domains is cast as a repeated game.
PROJECT
PARTICIPANTS
TEAMCORE MEMBERS | TEAMCORE ALUMNI | |
Lucia Gordon |
Debarun Kar |
COLLABORATORS
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
Rob Hannaford, Air Shepherd
RELATED
PUBLICATIONS
Harvard CRCS Workshop on AI for Social Good, 2020 Lily Xu, Andrew Perrault, Andrew Plumptre, Margaret Driciru, Fred Wanyama, Aggrey Rwetsiba, and Milind Tambe |
Game Theory on the Ground: The Effect of Increased Patrols on Deterring Poachers |
Proceedings of the IEEE Winter Conference on Applications of Computer Vision (WACV), 2020 Elizabeth Bondi, Raghav Jain, Palash Aggrawal, Saket Anand, Robert Hannaford, Ashish Kapoor, Jim Piavis, Shital Shah, Lucas Joppa, Bistra Dilkina, Milind Tambe |
BIRDSAI: A Dataset for Detection and Tracking in Aerial Thermal Infrared Videos |
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI), 2020 Elizabeth Bondi, Hoon Oh, Haifeng Xu, Fei Fang, Bistra Dilkina, Milind Tambe |
To Signal or Not To Signal: Exploiting Uncertain Real-Time Information in Signaling Games for Security and Sustainability |
IEEE International Conference on Data Engineering (ICDE-20)Lily Xu, Shahrzad Gholami, Sara Mc Carthy, Bistra Dilkina, Andrew Plumptre, Milind Tambe, Rohit Singh, Mustapha Nsubuga, Joshua Mabonga, Margaret Driciru, Fred Wanyama, Aggrey Rwetsiba, Tom Okello, Eric Enyel |
Stay Ahead of Poachers: Illegal Wildlife Poaching Prediction and Patrol Planning Under Uncertainty with Field Test Evaluations |
International Joint Conference on Artificial Intelligence Elizabeth Bondi, Hoon Oh, Haifeng Xu, Fei Fang, Bistra Dilkina, & Milind Tambe |
Biodiversity Conservation with Drones: Using Uncertain Real-Time Information in Signaling Games to Prevent Poaching |
International Conference on Machine Learning AI for Social Good Workshop Elizabeth Bondi, Hoon Oh, Haifeng Xu, Fei Fang, Bistra Dilkina, & Milind Tambe |
Wildlife GUARDSS: Using Uncertain Real-Time Information in Signaling Games for Sustainability |
In COMPASS ’18: ACM SIGCAS Conference on Computing and Sustainable Societies (COMPASS), June 20–22, 2018, Menlo Park and San Jose, CA, USA. ACM, New York, NY, USA. Elizabeth Bondi, Debadeepta Dey, Ashish Kapoor, Jim Piavis, Shital Shah, Fei Fang, Bistra Dilkina, Robert Hannaford, Arvind Iyer, Lucas Joppa, Milind Tambe |
AirSim-W: A Simulation Environment for Wildlife Conservation with UAVs |
International Conference on Autonomous Agents and Multiagent Systems (AAMAS-18), 2018 Haifeng Xu, Shaddin Dughmi, Milind Tambe, Venil Loyd Noronha |
Mitigating the Curse of Correlation in Security Games by Entropy Maximization (Extended Abstract) |
Proceedings of the Thirteenth International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2014 Rong Yang, Benjamin Ford, Milind Tambe, Andrew Lemieux |
Adaptive Resource Allocation for Wildlife Protection against Illegal Poachers |
Proceedings of the Thirteenth International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2014 Benjamin Ford, Debarun Kar, Francesco M. Delle Fave, Rong Yang, Milind Tambe |
PAWS: Adaptive Game-theoretic Patrolling for Wildlife Protection (Demonstration) |
6th Conference on Decision and Game Theory for Security (GameSec), 2015 Thanh H. Nguyen, Francesco M. Delle Fave, Debarun Kar, Aravind S. Lakshminarayanan, Amulya Yadav, Milind Tambe, Noa Agmon, Andrew J. Plumptre, Margaret Driciru, Fred Wanyama, Aggrey Rwetsiba |
Making the most of Our Regrets: Regret-based Solutions to Handle Payoff Uncertainty and Elicitation in Green Security Games |
International Joint Conference on Artificial Intelligence (IJCAI), 2015 Fei Fang, Peter Stone, Milind Tambe |
“A Game of Thrones”: When Human Behavior Models Compete in Repeated Stackelberg Security Games |
The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD Applied Data Science Track), 2017 Shahrzad Gholami, Benjamin Ford, Fei Fang, Andy Plumptre, Milind Tambe, Margaret Driciru, Fred Wanyama, Aggrey Rwetsiba, Mustafa Nsubaga, and Joshua Mabonga |
Taking it for a Test Drive: A Hybrid Spatio-temporal Model for Wildlife Poaching Prediction Evaluated through a Controlled Field Test |
AI Magazine, 2017 Fei Fang, Thanh H. Nguyen, Rob Pickles, Wai Y. Lam, Gopalasamy R. Clements, Bo An, Amandeep Singh, Brian C. Schwedock, Milind Tambe, Andrew Lemieux |
PAWS – A Deployed Game-Theoretic Application to Combat Poaching |
Proceedings of the 15th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2016 Thanh H. Nguyen, Arunesh Sinha, Shahrzad Gholami, Andrew J. Plumptre, Lucas Joppa, Milind Tambe, Margaret Driciru, Fred Wanyama, Aggrey Rwetsiba, Rob Critchlow, and Colin Beale |
CAPTURE: A New Predictive Anti-Poaching Tool for Wildlife Protection |
Innovative Applications of Artificial Intelligence Twenty-Eighth IAAI Conference (Winner of Deployed Application Award), January 2016 Fei Fang, Thanh H. Nguyen, Rob Pickles, Wai Y. Lam, Gopalasamy R. Clements, Bo An, Amandeep Singh, Milind Tambe, and Andrew Lemieux |
Deploying PAWS: Field Optimization of the Protection Assistant for Wildlife Security |
Proceedings of the 16th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2017 Debarun Kar and Benjamin Ford, Shahrzad Gholami, Fei Fang, Andrew Plumptre, Milind Tambe, Margaret Driciru, Fred Wanyama, Aggrey Rwetsiba |
Cloudy with a Chance of Poaching: Adversary Behavior Modeling and Forecasting with Real-World Poaching Data |
PhD thesis, August 2017 Benjamin Ford |
Real-World Evaluation and Deployment of Wildlife Crime Prediction Models |
Conference on Decision and Game Theory for Security (GameSec), 2017 Elizabeth Bondi, Fei Fang, Debarun Kar, Venil Noronha, Donnabell Dmello, Milind Tambe, Arvind Iyer, and Robert Hannaford |
VIOLA: Video Labeling Application for Security Domains |
In IWAISe: 1st International Workshop on A.I. in Security held at the International Joint Conference on Artificial Intelligence, 2017 Nitin Kamra, Fei Fang, Debarun Kar, Yan Liu, Milind Tambe |
Handling Continuous Space Security Games with Neural Networks |
PhD thesis, June 2017 Debarun Kar |
When AI helps Wildlife Conservation: Learning Adversary Behaviors in Green Security Games |
Proceedings of the Thirtieth Annual Conference on Innovative Applications of Artificial Intelligence (IAAI-18), February 2018 Elizabeth Bondi, Fei Fang, Mark Hamilton, Debarun Kar, Donnabell Dmello, Jongmoo Choi, Robert Hannaford, Arvind Iyer, Lucas Joppa, Milind Tambe, Ram Nevatia |
SPOT Poachers in Action: Augmenting Conservation Drones with Automatic Detection in Near Real Time |
AAAI conference on Artificial Intelligence (AAAI-18), 2018 Shahrzad Gholami, Benjamin Ford, Debarun Kar, Fei Fang, Milind Tambe, Andrew Plumptre, Margaret Driciru, Fred Wanyama, Aggrey Rwetsiba, Mustapha Nsubaga, Joshua Mabonga |
Evaluation of Predictive Models for Wildlife Poaching Activity through Controlled Field Test in Uganda |
AAAI conference on Artificial Intelligence (AAAI-18), 2018 Shahrzad Gholami |
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International Conference on Autonomous Agents and Multi-agent Systems (AAMAS 2018), 2018 Shahrzad Gholami, Sara Mc Carthy, Bistra Dilkina, Andrew Plumptre, Milind Tambe, Margaret Driciru, Fred Wanyama, Aggrey Rwetsiba, Mustapha Nsubaga, Joshua Mabonga, Tom Okello, Eric Enyel |
Adversary models account for imperfect crime data: Forecasting and planning against real-world poachers (Corrected Version) |