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- research-articleMay 2019
Don't Put All Your Strategies in One Basket: Playing Green Security Games with Imperfect Prior Knowledge
AAMAS '19: Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent SystemsPages 395–403Security efforts for wildlife monitoring and protection of endangered species (e.g., elephants, rhinos, etc.) are constrained by limited resources available to law enforcement agencies. Recent progress in Green Security Games (GSGs) has led to patrol ...
- research-articleJuly 2018
Adversary Models Account for Imperfect Crime Data: Forecasting and Planning against Real-world Poachers
- 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
AAMAS '18: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent SystemsPages 823–831Poachers are engaged in extinction level wholesale slaughter, so it is critical to harness historical data for predicting poachers' behavior. However, in these domains, data collected about adversarial actions are remarkably imperfect, where reported ...
- extended-abstractMay 2017
On Repeated Stackelberg Security Game with the Cooperative Human Behavior Modelfor Wildlife Protection
AAMAS '17: Proceedings of the 16th Conference on Autonomous Agents and MultiAgent SystemsPages 1751–1753Inspired by successful deployments of Stackelberg Security Game in real life, researchers are working hard to optimize the game models to make them more practical. Recent security game work on wildlife protection makes a step forward by taking the ...
- research-articleMay 2016
CAPTURE: A New Predictive Anti-Poaching Tool for Wildlife Protection
- Thanh H. Nguyen,
- Arunesh Sinha,
- Shahrzad Gholami,
- Andrew Plumptre,
- Lucas Joppa,
- Milind Tambe,
- Margaret Driciru,
- Fred Wanyama,
- Aggrey Rwetsiba,
- Rob Critchlow,
- Colin M. Beale
AAMAS '16: Proceedings of the 2016 International Conference on Autonomous Agents & Multiagent SystemsPages 767–775Wildlife poaching presents a serious extinction threat to many animal species. Agencies ("defenders") focused on protecting such animals need tools that help analyze, model and predict poacher activities, so they can more effectively combat such ...
- research-articleMay 2016
Learning Adversary Behavior in Security Games: A PAC Model Perspective
AAMAS '16: Proceedings of the 2016 International Conference on Autonomous Agents & Multiagent SystemsPages 214–222Recent applications of Stackelberg Security Games (SSG), from wildlife crime to urban crime, have employed machine learning tools to learn and predict adversary behavior using available data about defender-adversary interactions. Given these recent ...
- research-articleMay 2014
Adaptive resource allocation for wildlife protection against illegal poachers
AAMAS '14: Proceedings of the 2014 international conference on Autonomous agents and multi-agent systemsPages 453–460Illegal poaching is an international problem that leads to the extinction of species and the destruction of ecosystems. As evidenced by dangerously dwindling populations of endangered species, existing anti-poaching mechanisms are insufficient. This ...
