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Milind Tambe | Kai Wang | Elizabeth Bondi | Lily Xu | Andrew Perrault | Fei Fang | Milind Tambe | Fei Fang | A. Perrault | Lily Xu | Kai Wang | Elizabeth Bondi-Kelly
[1] Alexandre Proutière,et al. Lipschitz Bandits: Regret Lower Bound and Optimal Algorithms , 2014, COLT.
[2] Nicola Basilico,et al. Leader-follower strategies for robotic patrolling in environments with arbitrary topologies , 2009, AAMAS.
[3] Nicholas R. Jennings,et al. Playing Repeated Security Games with No Prior Knowledge , 2016, AAMAS.
[4] Peter Auer,et al. Finite-time Analysis of the Multiarmed Bandit Problem , 2002, Machine Learning.
[5] Milind Tambe,et al. When Security Games Go Green: Designing Defender Strategies to Prevent Poaching and Illegal Fishing , 2015, IJCAI.
[6] Haifeng Xu,et al. Optimal Patrol Planning for Green Security Games with Black-Box Attackers , 2017, GameSec.
[7] A. Lemieux,et al. Poaching in Uganda: Perspectives of Law Enforcement Rangers , 2015 .
[8] A. Plumptre,et al. Spatiotemporal trends of illegal activities from ranger‐collected data in a Ugandan national park , 2015, Conservation biology : the journal of the Society for Conservation Biology.
[9] Long Tran-Thanh,et al. Don't Put All Your Strategies in One Basket: Playing Green Security Games with Imperfect Prior Knowledge , 2019, AAMAS.
[10] Csaba Szepesvári,et al. –armed Bandits , 2022 .
[11] Milind Tambe,et al. Stay Ahead of Poachers: Illegal Wildlife Poaching Prediction and Patrol Planning Under Uncertainty with Field Test Evaluations (Short Version) , 2019, 2020 IEEE 36th International Conference on Data Engineering (ICDE).
[12] Bo An,et al. Deploying PAWS: Field Optimization of the Protection Assistant for Wildlife Security , 2016, AAAI.
[13] Milind Tambe,et al. Adversary Models Account for Imperfect Crime Data: Forecasting and Planning against Real-world Poachers , 2018, AAMAS.
[14] Yajun Wang,et al. Combinatorial Multi-Armed Bandit and Its Extension to Probabilistically Triggered Arms , 2014, J. Mach. Learn. Res..
[15] Robert D. Kleinberg. Nearly Tight Bounds for the Continuum-Armed Bandit Problem , 2004, NIPS.
[16] Thorsten Joachims,et al. Multi-armed Bandit Problems with History , 2012, AISTATS.
[17] Santiago Ontañón,et al. Regression Oracles and Exploration Strategies for Short-Horizon Multi-Armed Bandits , 2020, 2020 IEEE Conference on Games (CoG).
[18] Santosh S. Vempala,et al. Efficient algorithms for online decision problems , 2005, J. Comput. Syst. Sci..
[19] Milind Tambe,et al. CAPTURE: A New Predictive Anti-Poaching Tool for Wildlife Protection , 2016, AAMAS.
[20] Eli Upfal,et al. Bandits and Experts in Metric Spaces , 2013, J. ACM.
[21] Milind Tambe,et al. Robust Protection of Fisheries with COmPASS , 2014, AAAI.
[22] Csaba Szepesvari,et al. Bandit Algorithms , 2020 .
[23] Yan Liu,et al. Policy Learning for Continuous Space Security Games Using Neural Networks , 2018, AAAI.
[24] Eli Upfal,et al. Multi-Armed Bandits in Metric Spaces ∗ , 2008 .
[25] Douglas J. Lober. Using forest guards to protect a biological reserve in Costa Rica: one step towards linking parks to people , 1992 .
[26] Milind Tambe,et al. Preventing Illegal Logging: Simultaneous Optimization of Resource Teams and Tactics for Security , 2016, AAAI.
[27] Ariel D. Procaccia,et al. Learning Optimal Commitment to Overcome Insecurity , 2014, NIPS.
[28] Sébastien Bubeck,et al. Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems , 2012, Found. Trends Mach. Learn..
[29] Grace Nangendo,et al. Efficiently targeting resources to deter illegal activities in protected areas , 2014 .