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ORCIDFei Fang 0001
Person information
- affiliation: Carnegie Mellon University, Pittsburgh, PA, USA
Other persons with the same name
- Fei Fang — disambiguation page
- Fei Fang 0002
![[0009-0001-6535-5553]](https://dblp.org/img/orcid-mark.12x12.png "0009-0001-6535-5553")
— Alibaba Group, Beijing, China - Fei Fang 0003 — Beijing Technology and Business University, Department of Mathematics, Beijing, China
- Fei Fang 0004 — Peking University, School of New Media, Beijing, China
- Fei Fang 0005 — Stanford University, Stanford, CA, USA
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2020 – today
- 2024
[j16]Weiran Shen, Minbiao Han, Weizhe Chen, Taoan Huang, Rohit Singh, Haifeng Xu, Fei Fang:
An extensive study of security games with strategic informants. Artif. Intell. 334: 104162 (2024)- [j15]Stephanie Milani, Nicholay Topin, Manuela Veloso, Fei Fang:
Explainable Reinforcement Learning: A Survey and Comparative Review. ACM Comput. Surv. 56(7): 168:1-168:36 (2024) - [c98]Yixuan Even Xu, Chun Kai Ling, Fei Fang:
Learning Coalition Structures with Games. AAAI 2024: 9944-9951 - [c97]Jiayu Chen, Zelai Xu, Yunfei Li, Chao Yu, Jiaming Song, Huazhong Yang, Fei Fang, Yu Wang, Yi Wu:
Accelerate Multi-Agent Reinforcement Learning in Zero-Sum Games with Subgame Curriculum Learning. AAAI 2024: 11320-11328 - [c96]Sameer Jain, Sedrick Scott Keh, Shova Chettri, Karun Dewan, Pablo Izquierdo, Johanna Prussman, Pooja Shrestha, César Suárez, Zheyuan Ryan Shi, Lei Li, Fei Fang:
Where It Really Matters: Few-Shot Environmental Conservation Media Monitoring for Low-Resource Languages. AAAI 2024: 22141-22149 - [c95]Aravind Venugopal, Stephanie Milani, Fei Fang, Balaraman Ravindran:
MABL: Bi-Level Latent-Variable World Model for Sample-Efficient Multi-Agent Reinforcement Learning. AAMAS 2024: 1865-1873 - [c94]Zhicheng Zhang, Yancheng Liang, Yi Wu, Fei Fang:
MESA: Cooperative Meta-Exploration in Multi-Agent Learning through Exploiting State-Action Space Structure. AAMAS 2024: 2085-2093 - [c93]Zelai Xu, Chao Yu, Fei Fang, Yu Wang, Yi Wu:
Language Agents with Reinforcement Learning for Strategic Play in the Werewolf Game. ICML 2024 - [c92]Zheyuan Ryan Shi, Jiayin Zhi, Siqi Zeng, Zhicheng Zhang, Ameesh Kapoor, Sean Hudson, Hong Shen, Fei Fang:
Predicting and Presenting Task Difficulty for Crowdsourcing Food Rescue Platforms. WWW 2024: 4686-4696 - [i64]Steven Jecmen, Nihar B. Shah, Fei Fang, Leman Akoglu:
On the Detection of Reviewer-Author Collusion Rings From Paper Bidding. CoRR abs/2402.07860 (2024) - [i63]Sameer Jain, Sedrick Scott Keh, Shova Chettri, Karun Dewan, Pablo Izquierdo, Johanna Prussman, Pooja Shrestha, César Suárez, Zheyuan Ryan Shi, Lei Li, Fei Fang:
Where It Really Matters: Few-Shot Environmental Conservation Media Monitoring for Low-Resource Languages. CoRR abs/2402.11818 (2024) - [i62]Rex Chen, Ruiyi Wang, Norman Sadeh, Fei Fang:
Missing Pieces: How Framing Uncertainty Impacts Longitudinal Trust in AI Decision Aids - A Gig Driver Case Study. CoRR abs/2404.06432 (2024) - [i61]Zhicheng Zhang, Yancheng Liang, Yi Wu, Fei Fang:
MESA: Cooperative Meta-Exploration in Multi-Agent Learning through Exploiting State-Action Space Structure. CoRR abs/2405.00902 (2024) - [i60]Ruiyi Wang, Stephanie Milani, Jamie C. Chiu, Shaun M. Eack, Travis Labrum, Samuel M. Murphy, Nev Jones, Kate Hardy, Hong Shen, Fei Fang, Zhiyu Zoey Chen:
PATIENT-Ψ: Using Large Language Models to Simulate Patients for Training Mental Health Professionals. CoRR abs/2405.19660 (2024) - [i59]Ziyan Wang, Meng Fang, Tristan Tomilin, Fei Fang, Yali Du:
Safe Multi-agent Reinforcement Learning with Natural Language Constraints. CoRR abs/2405.20018 (2024) - [i58]Naveen Raman, Zheyuan Ryan Shi, Fei Fang:
Global Rewards in Restless Multi-Armed Bandits. CoRR abs/2406.00738 (2024) - [i57]Jingwu Tang, Gokul Swamy, Fei Fang, Zhiwei Steven Wu:
Multi-Agent Imitation Learning: Value is Easy, Regret is Hard. CoRR abs/2406.04219 (2024) - [i56]Zhuorui Ye, Stephanie Milani, Geoffrey J. Gordon, Fei Fang:
Concept-Based Interpretable Reinforcement Learning with Limited to No Human Labels. CoRR abs/2407.15786 (2024) - 2023
- [c91]Chun Kai Ling, J. Zico Kolter, Fei Fang:
Function Approximation for Solving Stackelberg Equilibrium in Large Perfect Information Games. AAAI 2023: 5764-5772 - [c90]Sedrick Scott Keh, Zheyuan Ryan Shi, David J. Patterson, Nirmal Bhagabati, Karun Dewan, Areendran Gopala, Pablo Izquierdo, Debojyoti Mallick, Ambika Sharma, Pooja Shrestha, Fei Fang:
NewsPanda: Media Monitoring for Timely Conservation Action. AAAI 2023: 15528-15536 - [c89]Stephanie Milani, Arthur Juliani, Ida Momennejad, Raluca Georgescu, Jaroslaw Rzepecki, Alison Shaw, Gavin Costello, Fei Fang, Sam Devlin, Katja Hofmann:
Navigates Like Me: Understanding How People Evaluate Human-Like AI in Video Games. CHI 2023: 572:1-572:18 - [c88]Zimeng Song, Chun Kai Ling, Fei Fang:
Multi-defender Security Games with Schedules. GameSec 2023: 65-85 - [c87]Yue Guo, Joseph Campbell, Simon Stepputtis, Ruiyu Li, Dana Hughes, Fei Fang, Katia P. Sycara:
Explainable Action Advising for Multi-Agent Reinforcement Learning. ICRA 2023: 5515-5521 - [c86]Yixuan Xu, Steven Jecmen, Zimeng Song, Fei Fang:
A One-Size-Fits-All Approach to Improving Randomness in Paper Assignment. NeurIPS 2023 - [c85]Ravdeep S. Pasricha, Uday Singh Saini, Nicholas D. Sidiropoulos, Fei Fang, Kevin Chan, Evangelos E. Papalexakis:
Harvester: Principled Factorization-based Temporal Tensor Granularity Estimation. SDM 2023: 82-90 - [c84]Rex Chen, Kathleen M. Carley, Fei Fang, Norman M. Sadeh:
Purpose in the Machine: Do Traffic Simulators Produce Distributionally Equivalent Outcomes for Reinforcement Learning Applications? WSC 2023: 1842-1853 - [c83]Steven Jecmen, Minji Yoon, Vincent Conitzer, Nihar B. Shah, Fei Fang:
A Dataset on Malicious Paper Bidding in Peer Review. WWW 2023: 3816-3826 - [e3]Fei Fang, Haifeng Xu, Yezekael Hayel:
Decision and Game Theory for Security - 13th International Conference, GameSec 2022, Pittsburgh, PA, USA, October 26-28, 2022, Proceedings. Lecture Notes in Computer Science 13727, Springer 2023, ISBN 978-3-031-26368-2 [contents] - [i55]Stephanie Milani, Arthur Juliani, Ida Momennejad, Raluca Georgescu, Jaroslaw Rzepecki, Alison Shaw, Gavin Costello, Fei Fang, Sam Devlin, Katja Hofmann:
Navigates Like Me: Understanding How People Evaluate Human-Like AI in Video Games. CoRR abs/2303.02160 (2023) - [i54]Aravind Venugopal, Stephanie Milani, Fei Fang, Balaraman Ravindran:
Bi-level Latent Variable Model for Sample-Efficient Multi-Agent Reinforcement Learning. CoRR abs/2304.06011 (2023) - [i53]Sedrick Scott Keh, Zheyuan Ryan Shi, David J. Patterson, Nirmal Bhagabati, Karun Dewan, Areendran Gopala, Pablo Izquierdo, Debojyoti Mallick, Ambika Sharma, Pooja Shrestha, Fei Fang:
NewsPanda: Media Monitoring for Timely Conservation Action. CoRR abs/2305.01503 (2023) - [i52]Ryan Liu, Steven Jecmen, Vincent Conitzer, Fei Fang, Nihar B. Shah:
Testing for Reviewer Anchoring in Peer Review: A Randomized Controlled Trial. CoRR abs/2307.05443 (2023) - [i51]Jiayu Chen, Zelai Xu, Yunfei Li, Chao Yu, Jiaming Song, Huazhong Yang, Fei Fang, Yu Wang, Yi Wu:
Accelerate Multi-Agent Reinforcement Learning in Zero-Sum Games with Subgame Curriculum Learning. CoRR abs/2310.04796 (2023) - [i50]Yixuan Even Xu, Steven Jecmen, Zimeng Song, Fei Fang:
A One-Size-Fits-All Approach to Improving Randomness in Paper Assignment. CoRR abs/2310.05995 (2023) - [i49]Zelai Xu, Chao Yu, Fei Fang, Yu Wang, Yi Wu:
Language Agents with Reinforcement Learning for Strategic Play in the Werewolf Game. CoRR abs/2310.18940 (2023) - [i48]Rex Chen, Kathleen M. Carley, Fei Fang, Norman M. Sadeh:
Purpose in the Machine: Do Traffic Simulators Produce Distributionally Equivalent Outcomes for Reinforcement Learning Applications? CoRR abs/2311.08429 (2023) - [i47]Zimeng Song, Chun Kai Ling, Fei Fang:
Multi-defender Security Games with Schedules. CoRR abs/2311.16392 (2023) - [i46]Yixuan Even Xu, Chun Kai Ling, Fei Fang:
Learning Coalition Structures with Games. CoRR abs/2312.09058 (2023) - 2022
- [j14]Hongyao Ma, Fei Fang, David C. Parkes:
Spatio-Temporal Pricing for Ridesharing Platforms. Oper. Res. 70(2): 1025-1041 (2022) - [j13]Yawen Wu, Zhenge Jia, Fei Fang, Jingtong Hu:
Cooperative Communication Between Two Transiently Powered Sensor Nodes by Reinforcement Learning. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 41(1): 76-90 (2022) - [c82]Chun Kai Ling, Fei Fang:
Safe Subgame Resolving for Extensive Form Correlated Equilibrium. AAAI 2022: 5116-5123 - [c81]Zheyuan Ryan Shi, Zhiwei Steven Wu, Rayid Ghani, Fei Fang:
Bandit Data-Driven Optimization for Crowdsourcing Food Rescue Platforms. AAAI 2022: 12154-12162 - [c80]Steven Jecmen, Hanrui Zhang, Ryan Liu, Fei Fang, Vincent Conitzer, Nihar B. Shah:
Near-Optimal Reviewer Splitting in Two-Phase Paper Reviewing and Conference Experiment Design. AAMAS 2022: 1642-1644 - [c79]Steven Jecmen, Hanrui Zhang, Ryan Liu, Fei Fang, Vincent Conitzer, Nihar B. Shah:
Near-Optimal Reviewer Splitting in Two-Phase Paper Reviewing and Conference Experiment Design. HCOMP 2022: 102-113 - [c78]Rex Chen, Fei Fang, Norman M. Sadeh:
The Real Deal: A Review of Challenges and Opportunities in Moving Reinforcement Learning-Based Traffic Signal Control Systems Towards Reality. ATT@IJCAI 2022: 14-31 - [c77]Peide Huang, Mengdi Xu, Fei Fang, Ding Zhao:
Robust Reinforcement Learning as a Stackelberg Game via Adaptively-Regularized Adversarial Training. IJCAI 2022: 3099-3106 - [c76]Lily Xu, Arpita Biswas, Fei Fang, Milind Tambe:
Ranked Prioritization of Groups in Combinatorial Bandit Allocation. IJCAI 2022: 5206-5212 - [c75]Peide Huang, Mengdi Xu, Jiacheng Zhu, Laixi Shi, Fei Fang, Ding Zhao:
Curriculum Reinforcement Learning using Optimal Transport via Gradual Domain Adaptation. NeurIPS 2022 - [c74]Jibang Wu, Weiran Shen, Fei Fang, Haifeng Xu:
Inverse Game Theory for Stackelberg Games: the Blessing of Bounded Rationality. NeurIPS 2022 - [c73]Guan Yang, Minghuan Liu, Weijun Hong, Weinan Zhang, Fei Fang, Guangjun Zeng, Yue Lin:
PerfectDou: Dominating DouDizhu with Perfect Information Distillation. NeurIPS 2022 - [c72]Stephanie Milani, Zhicheng Zhang, Nicholay Topin, Zheyuan Ryan Shi, Charles A. Kamhoua, Evangelos E. Papalexakis, Fei Fang:
MAVIPER: Learning Decision Tree Policies for Interpretable Multi-agent Reinforcement Learning. ECML/PKDD (4) 2022: 251-266 - [e2]Francisco S. Melo, Fei Fang:
Autonomous Agents and Multiagent Systems. Best and Visionary Papers - AAMAS 2022 Workshops, Virtual Event, May 9-13, 2022, Revised Selected Papers. Lecture Notes in Computer Science 13441, Springer 2022, ISBN 978-3-031-20178-3 [contents] - [i45]Stephanie Milani, Nicholay Topin, Manuela Veloso, Fei Fang:
A Survey of Explainable Reinforcement Learning. CoRR abs/2202.08434 (2022) - [i44]Peide Huang, Mengdi Xu, Fei Fang, Ding Zhao:
Robust Reinforcement Learning as a Stackelberg Game via Adaptively-Regularized Adversarial Training. CoRR abs/2202.09514 (2022) - [i43]Yang Guan, Minghuan Liu, Weijun Hong, Weinan Zhang, Fei Fang, Guangjun Zeng, Yue Lin:
PerfectDou: Dominating DouDizhu with Perfect Information Distillation. CoRR abs/2203.16406 (2022) - [i42]Lily Xu, Arpita Biswas, Fei Fang, Milind Tambe:
Ranked Prioritization of Groups in Combinatorial Bandit Allocation. CoRR abs/2205.05659 (2022) - [i41]Stephanie Milani, Zhicheng Zhang, Nicholay Topin, Zheyuan Ryan Shi, Charles A. Kamhoua, Evangelos E. Papalexakis, Fei Fang:
MAVIPER: Learning Decision Tree Policies for Interpretable Multi-Agent Reinforcement Learning. CoRR abs/2205.12449 (2022) - [i40]Rex Chen, Fei Fang, Norman M. Sadeh:
The Real Deal: A Review of Challenges and Opportunities in Moving Reinforcement Learning-Based Traffic Signal Control Systems Towards Reality. CoRR abs/2206.11996 (2022) - [i39]Steven Jecmen, Minji Yoon, Vincent Conitzer, Nihar B. Shah, Fei Fang:
A Dataset on Malicious Paper Bidding in Peer Review. CoRR abs/2207.02303 (2022) - [i38]Steven Jecmen, Nihar B. Shah, Fei Fang, Vincent Conitzer:
Tradeoffs in Preventing Manipulation in Paper Bidding for Reviewer Assignment. CoRR abs/2207.11315 (2022) - [i37]Jibang Wu, Weiran Shen, Fei Fang, Haifeng Xu:
Inverse Game Theory for Stackelberg Games: the Blessing of Bounded Rationality. CoRR abs/2210.01380 (2022) - [i36]Peide Huang, Mengdi Xu, Jiacheng Zhu, Laixi Shi, Fei Fang, Ding Zhao:
Curriculum Reinforcement Learning using Optimal Transport via Gradual Domain Adaptation. CoRR abs/2210.10195 (2022) - [i35]Yue Guo, Joseph Campbell, Simon Stepputtis, Ruiyu Li, Dana Hughes, Fei Fang, Katia P. Sycara:
Explainable Action Advising for Multi-Agent Reinforcement Learning. CoRR abs/2211.07882 (2022) - [i34]Chun Kai Ling, Fei Fang:
Safe Subgame Resolving for Extensive Form Correlated Equilibrium. CoRR abs/2212.14317 (2022) - [i33]Chun Kai Ling, J. Zico Kolter, Fei Fang:
Function Approximation for Solving Stackelberg Equilibrium in Large Perfect Information Games. CoRR abs/2212.14431 (2022) - 2021
- [j12]Fei Fang:
AGNT SI: agents and multiagent systems for social good. Auton. Agents Multi Agent Syst. 35(2): 43 (2021) - [c71]Nicholay Topin, Stephanie Milani, Fei Fang, Manuela Veloso:
Iterative Bounding MDPs: Learning Interpretable Policies via Non-Interpretable Methods. AAAI 2021: 9923-9931 - [c70]Lily Xu, Elizabeth Bondi, Fei Fang, Andrew Perrault, Kai Wang, Milind Tambe:
Dual-Mandate Patrols: Multi-Armed Bandits for Green Security. AAAI 2021: 14974-14982 - [c69]Weizhe Chen, Weinan Zhang, Duo Liu, Weiping Li, Xiaojun Shi, Fei Fang:
Data-Driven Multimodal Patrol Planning for Anti-poaching. AAAI 2021: 15270-15277 - [c68]Fei Fang:
Game Theoretic Models for Cyber Deception. MTD@CCS 2021: 23-24 - [c67]Liheng Chen, Hongyi Guo, Yali Du, Fei Fang, Haifeng Zhang, Weinan Zhang, Yong Yu:
Signal Instructed Coordination in Cooperative Multi-agent Reinforcement Learning. DAI 2021: 185-205 - [c66]Alison Hau, Fei Fang, Zheyuan Ryan Shi:
Poster: Pallet Estimation for Food Bank Logistics Management. COMPASS 2021: 385-388 - [c65]Zhenggang Tang, Chao Yu, Boyuan Chen, Huazhe Xu, Xiaolong Wang, Fei Fang, Simon Shaolei Du, Yu Wang, Yi Wu:
Discovering Diverse Multi-Agent Strategic Behavior via Reward Randomization. ICLR 2021 - [c64]Weizhe Chen, Zihan Zhou, Yi Wu, Fei Fang:
Temporal Induced Self-Play for Stochastic Bayesian Games. IJCAI 2021: 96-103 - [c63]Lily Xu, Andrew Perrault, Fei Fang, Haipeng Chen, Milind Tambe:
Robust reinforcement learning under minimax regret for green security. UAI 2021: 257-267 - [c62]Rex Chen, Fei Fang, Thomas B. Norton, Aleecia M. McDonald, Norman M. Sadeh:
Fighting the Fog: Evaluating the Clarity of Privacy Disclosures in the Age of CCPA. WPES@CCS 2021: 73-102 - [c61]Zheyuan Ryan Shi, Leah Lizarondo, Fei Fang:
A Recommender System for Crowdsourcing Food Rescue Platforms. WWW 2021: 857-865 - [i32]Nicholay Topin, Stephanie Milani, Fei Fang, Manuela Veloso:
Iterative Bounding MDPs: Learning Interpretable Policies via Non-Interpretable Methods. CoRR abs/2102.13045 (2021) - [i31]Zhenggang Tang, Chao Yu, Boyuan Chen, Huazhe Xu, Xiaolong Wang, Fei Fang, Simon S. Du, Yu Wang, Yi Wu:
Discovering Diverse Multi-Agent Strategic Behavior via Reward Randomization. CoRR abs/2103.04564 (2021) - [i30]Lily Xu, Andrew Perrault, Fei Fang, Haipeng Chen, Milind Tambe:
Robust Reinforcement Learning Under Minimax Regret for Green Security. CoRR abs/2106.08413 (2021) - [i29]Steven Jecmen, Hanrui Zhang, Ryan Liu, Fei Fang, Vincent Conitzer, Nihar B. Shah:
Near-Optimal Reviewer Splitting in Two-Phase Paper Reviewing and Conference Experiment Design. CoRR abs/2108.06371 (2021) - [i28]Weizhe Chen, Zihan Zhou, Yi Wu, Fei Fang:
Temporal Induced Self-Play for Stochastic Bayesian Games. CoRR abs/2108.09444 (2021) - [i27]Rex Chen, Fei Fang, Thomas B. Norton, Aleecia M. McDonald, Norman M. Sadeh:
Fighting the Fog: Evaluating the Clarity of Privacy Disclosures in the Age of CCPA. CoRR abs/2109.13816 (2021) - [i26]Hoon Oh, Yanhan Tang, Zong Zhang, Alexandre Jacquillat, Fei Fang:
Efficiency, Fairness, and Stability in Non-Commercial Peer-to-Peer Ridesharing. CoRR abs/2110.01152 (2021) - 2020
- [j11]Andrew Perrault, Fei Fang, Arunesh Sinha, Milind Tambe:
Artificial Intelligence for Social Impact: Learning and Planning in the Data-to-Deployment Pipeline. AI Mag. 41(4): 3-16 (2020) - [j10]Hongyao Ma, Fei Fang, David C. Parkes:
Spatio-temporal pricing for ridesharing platforms. SIGecom Exch. 18(2): 53-57 (2020) - [c60]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. AAAI 2020: 1369-1377 - [c59]Zheyuan Ryan Shi, Aaron Schlenker, Brian Hay, Daniel Bittleston, Siyu Gao, Emily Peterson, John Trezza, Fei Fang:
Draining the Water Hole: Mitigating Social Engineering Attacks with CyberTWEAK. AAAI 2020: 13363-13368 - [c58]Zheyuan Ryan Shi, Yiwen Yuan, Kimberly Lo, Leah Lizarondo, Fei Fang:
Improving Efficiency of Volunteer-Based Food Rescue Operations. AAAI 2020: 13369-13375 - [c57]Taoan Huang, Weiran Shen, David Zeng, Tianyu Gu, Rohit Singh, Fei Fang:
Green Security Game with Community Engagement. AAMAS 2020: 529-537 - [c56]Zheyuan Ryan Shi, Ariel D. Procaccia, Kevin S. Chan, Sridhar Venkatesan, Noam Ben-Asher, Nandi O. Leslie, Charles A. Kamhoua, Fei Fang:
Learning and Planning in the Feature Deception Problem. GameSec 2020: 23-44 - [c55]Stephanie Milani, Weiran Shen, Kevin S. Chan, Sridhar Venkatesan, Nandi O. Leslie, Charles A. Kamhoua, Fei Fang:
Harnessing the Power of Deception in Attack Graph-Based Security Games. GameSec 2020: 147-167 - [c54]Qian Long, Zihan Zhou, Abhinav Gupta, Fei Fang, Yi Wu, Xiaolong Wang:
Evolutionary Population Curriculum for Scaling Multi-Agent Reinforcement Learning. ICLR 2020 - [c53]Weiran Shen, Weizhe Chen, Taoan Huang, Rohit Singh, Fei Fang:
When to Follow the Tip: Security Games with Strategic Informants. IJCAI 2020: 371-377 - [c52]Steven Jecmen, Hanrui Zhang, Ryan Liu, Nihar B. Shah, Vincent Conitzer, Fei Fang:
Mitigating Manipulation in Peer Review via Randomized Reviewer Assignments. NeurIPS 2020 - [c51]Chun Kai Ling, Fei Fang, J. Zico Kolter:
Deep Archimedean Copulas. NeurIPS 2020 - [p1]Aaron Schlenker, Omkar Thakoor, Haifeng Xu, Fei Fang, Milind Tambe, Phebe Vayanos:
Game Theoretic Cyber Deception to Foil Adversarial Network Reconnaissance. Adaptive Autonomous Secure Cyber Systems 2020: 183-204 - [i25]Andrew Perrault, Fei Fang, Arunesh Sinha, Milind Tambe:
AI for Social Impact: Learning and Planning in the Data-to-Deployment Pipeline. CoRR abs/2001.00088 (2020) - [i24]Zheyuan Ryan Shi, Claire Wang, Fei Fang:
Artificial Intelligence for Social Good: A Survey. CoRR abs/2001.01818 (2020) - [i23]Taoan Huang, Weiran Shen, David Zeng, Tianyu Gu, Rohit Singh, Fei Fang:
Green Security Game with Community Engagement. CoRR abs/2002.09126 (2020) - [i22]Qian Long, Zihan Zhou, Abhinav Gupta, Fei Fang, Yi Wu, Xiaolong Wang:
Evolutionary Population Curriculum for Scaling Multi-Agent Reinforcement Learning. CoRR abs/2003.10423 (2020) - [i21]Steven Jecmen, Hanrui Zhang, Ryan Liu, Nihar B. Shah, Vincent Conitzer, Fei Fang:
Mitigating Manipulation in Peer Review via Randomized Reviewer Assignments. CoRR abs/2006.16437 (2020) - [i20]Zheyuan Ryan Shi, Zhiwei Steven Wu, Rayid Ghani, Fei Fang:
Bandit Data-driven Optimization: AI for Social Good and Beyond. CoRR abs/2008.11707 (2020) - [i19]Lily Xu, Elizabeth Bondi, Fei Fang, Andrew Perrault, Kai Wang, Milind Tambe:
Dual-Mandate Patrols: Multi-Armed Bandits for Green Security. CoRR abs/2009.06560 (2020) - [i18]Chun Kai Ling, Fei Fang, J. Zico Kolter:
Deep Archimedean Copulas. CoRR abs/2012.03137 (2020)
2010 – 2019
- 2019
- [j9]Carla P. Gomes, Thomas G. Dietterich, Christopher Barrett, Jon Conrad, Bistra Dilkina, Stefano Ermon, Fei Fang, Andrew Farnsworth, Alan Fern, Xiaoli Z. Fern, Daniel Fink, Douglas H. Fisher, Alexander Flecker, Daniel Freund, Angela Fuller, John M. Gregoire, John E. Hopcroft, Steve Kelling, J. Zico Kolter, Warren B. Powell, Nicole D. Sintov, John S. Selker, Bart Selman, Daniel Sheldon, David B. Shmoys, Milind Tambe, Weng-Keen Wong, Christopher Wood, Xiaojian Wu, Yexiang Xue, Amulya Yadav, Abdul-Aziz Yakubu, Mary Lou Zeeman:
Computational sustainability: computing for a better world and a sustainable future. Commun. ACM 62(9): 56-65 (2019) - [c50]Yufei Wang, Zheyuan Ryan Shi, Lantao Yu, Yi Wu, Rohit Singh, Lucas Joppa, Fei Fang:
Deep Reinforcement Learning for Green Security Games with Real-Time Information. AAAI 2019: 1401-1408 - [c49]Qingyu Guo, Jiarui Gan, Fei Fang, Long Tran-Thanh, Milind Tambe, Bo An:
On the Inducibility of Stackelberg Equilibrium for Security Games. AAAI 2019: 2020-2028 - [c48]Shihui Li, Yi Wu, Xinyue Cui, Honghua Dong, Fei Fang, Stuart Russell:
Robust Multi-Agent Reinforcement Learning via Minimax Deep Deterministic Policy Gradient. AAAI 2019: 4213-4220 - [c47]Chun Kai Ling, Fei Fang, J. Zico Kolter:
Large Scale Learning of Agent Rationality in Two-Player Zero-Sum Games. AAAI 2019: 6104-6111 - [c46]Elizabeth Bondi, Hoon Oh, Haifeng Xu, Fei Fang, Bistra Dilkina, Milind Tambe:
Broken Signals in Security Games: Coordinating Patrollers and Sensors in the Real World. AAMAS 2019: 1838-1840 - [c45]Taoan Huang, Bohui Fang, Hoon Oh, Xiaohui Bei, Fei Fang:
Optimal Trip-Vehicle Dispatch with Multi-Type Requests. AAMAS 2019: 2024-2026 - [c44]Nitin Kamra, Umang Gupta, Kai Wang, Fei Fang, Yan Liu, Milind Tambe:
Deep Fictitious Play for Games with Continuous Action Spaces. AAMAS 2019: 2042-2044 - [c43]Elizabeth Bondi, Hoon Oh, Haifeng Xu, Fei Fang, Bistra Dilkina, Milind Tambe:
Using Game Theory in Real Time in the Real World: A Conservation Case Study. AAMAS 2019: 2336-2338 - [c42]Yawen Wu, Zhenge Jia, Fei Fang, Jingtong Hu:
Cooperative communication between two transiently powered sensors by reinforcement learning: work-in-progress. CODES+ISSS 2019: 15:1-15:2 - [c41]Hongyao Ma, Fei Fang, David C. Parkes:
Spatio-Temporal Pricing for Ridesharing Platforms. EC 2019: 583 - [c40]Nitin Kamra, Umang Gupta, Kai Wang, Fei Fang, Yan Liu, Milind Tambe:
DeepFP for Finding Nash Equilibrium in Continuous Action Spaces. GameSec 2019: 238-258 - [c39]Omkar Thakoor, Milind Tambe, Phebe Vayanos, Haifeng Xu, Christopher Kiekintveld, Fei Fang:
Cyber Camouflage Games for Strategic Deception. GameSec 2019: 525-541 - [c38]Fei Fang:
Integrating Learning with Game Theory for Societal Challenges. IJCAI 2019: 6393-6397 - [c37]Cody Kinneer, Ryan Wagner, Fei Fang, Claire Le Goues, David Garlan:
Modeling observability in adaptive systems to defend against advanced persistent threats. MEMOCODE 2019: 10:1-10:11 - [c36]Gabriele Farina, Chun Kai Ling, Fei Fang, Tuomas Sandholm:
Efficient Regret Minimization Algorithm for Extensive-Form Correlated Equilibrium. NeurIPS 2019: 5187-5197 - [c35]Gabriele Farina, Chun Kai Ling, Fei Fang, Tuomas Sandholm:
Correlation in Extensive-Form Games: Saddle-Point Formulation and Benchmarks. NeurIPS 2019: 9229-9239 - [c34]Aaron M. Roth, Samantha Reig, Umang Bhatt, Jonathan Shulgach, Tamara Amin, Afsaneh Doryab, Fei Fang, Manuela Veloso:
A Robot's Expressive Language Affects Human Strategy and Perceptions in a Competitive Game. RO-MAN 2019: 1-8 - [c33]Taoan Huang, Bohui Fang, Xiaohui Bei, Fei Fang:
Dynamic Trip-Vehicle Dispatch with Scheduled and On-Demand Requests. UAI 2019: 250-260 - [i17]Zheyuan Ryan Shi, Aaron Schlenker, Brian Hay, Fei Fang:
Towards Thwarting Social Engineering Attacks. CoRR abs/1901.00586 (2019) - [i16]Gregory D. Hager, Ann W. Drobnis, Fei Fang, Rayid Ghani, Amy Greenwald, Terah Lyons, David C. Parkes, Jason Schultz, Suchi Saria, Stephen F. Smith, Milind Tambe:
Artificial Intelligence for Social Good. CoRR abs/1901.05406 (2019) - [i15]Chun Kai Ling, Fei Fang, J. Zico Kolter:
Large Scale Learning of Agent Rationality in Two-Player Zero-Sum Games. CoRR abs/1903.04101 (2019) - [i14]Zheyuan Ryan Shi, Ariel D. Procaccia, Kevin S. Chan, Sridhar Venkatesan, Noam Ben-Asher, Nandi O. Leslie, Charles A. Kamhoua, Fei Fang:
Learning and Planning in Feature Deception Games. CoRR abs/1905.04833 (2019) - [i13]Gabriele Farina, Chun Kai Ling, Fei Fang, Tuomas Sandholm:
Correlation in Extensive-Form Games: Saddle-Point Formulation and Benchmarks. CoRR abs/1905.12564 (2019) - [i12]Taoan Huang, Bohui Fang, Xiaohui Bei, Fei Fang:
Dynamic Trip-Vehicle Dispatch with Scheduled and On-Demand Requests. CoRR abs/1907.08739 (2019) - [i11]Liheng Chen, Hongyi Guo, Haifeng Zhang, Fei Fang, Yaoming Zhu, Ming Zhou, Weinan Zhang, Qing Wang, Yong Yu:
Signal Instructed Coordination in Team Competition. CoRR abs/1909.04224 (2019) - [i10]Aaron M. Roth, Samantha Reig, Umang Bhatt, Jonathan Shulgach, Tamara Amin, Afsaneh Doryab, Fei Fang, Manuela Veloso:
A Robot's Expressive Language Affects Human Strategy and Perceptions in a Competitive Game. CoRR abs/1910.11459 (2019) - [i9]Gabriele Farina, Chun Kai Ling, Fei Fang, Tuomas Sandholm:
Efficient Regret Minimization Algorithm for Extensive-Form Correlated Equilibrium. CoRR abs/1910.12450 (2019) - 2018
- [c32]Lantao Yu, Yi Wu, Rohit Singh, Lucas Joppa, Fei Fang:
Deep Reinforcement Learning for Green Security Game with Online Information. AAAI Workshops 2018: 325-333 - [c31]Shahrzad Gholami, Benjamin J. Ford, Debarun Kar, Fei Fang, Milind Tambe, Andrew J. 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 Workshops 2018: 344-347 - [c30]Nitin Kamra, Umang Gupta, Fei Fang, Yan Liu, Milind Tambe:
Policy Learning for Continuous Space Security Games Using Neural Networks. AAAI 2018: 1103-1112 - [c29]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 2018: 7741-7746 - [c28]Aaron Schlenker, Omkar Thakoor, Haifeng Xu, Fei Fang, Milind Tambe, Long Tran-Thanh, Phebe Vayanos, Yevgeniy Vorobeychik:
Deceiving Cyber Adversaries: A Game Theoretic Approach. AAMAS 2018: 892-900 - [c27]Qingyu Guo, Jiarui Gan, Fei Fang, Long Tran-Thanh, Milind Tambe, Bo An:
Inducible Equilibrium for Security Games. AAMAS 2018: 1947-1949 - [c26]Swaminathan Gurumurthy, Lantao Yu, Chenyan Zhang, Yongchao Jin, Weiping Li, Xiaodong Zhang, Fei Fang:
Exploiting Data and Human Knowledge for Predicting Wildlife Poaching. COMPASS 2018: 29:1-29:8 - [c25]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. COMPASS 2018: 40:1-40:12 - [c24]Chun Kai Ling, Fei Fang, J. Zico Kolter:
What Game Are We Playing? End-to-end Learning in Normal and Extensive Form Games. IJCAI 2018: 396-402 - [c23]Zheyuan Ryan Shi, Ziye Tang, Long Tran-Thanh, Rohit Singh, Fei Fang:
Designing the Game to Play: Optimizing Payoff Structure in Security Games. IJCAI 2018: 512-518 - [c22]Arunesh Sinha, Fei Fang, Bo An, Christopher Kiekintveld, Milind Tambe:
Stackelberg Security Games: Looking Beyond a Decade of Success. IJCAI 2018: 5494-5501 - [i8]Hongyao Ma, Fei Fang, David C. Parkes:
Spatio-Temporal Pricing for Ridesharing Platforms. CoRR abs/1801.04015 (2018) - [i7]Zheyuan Ryan Shi, Ziye Tang, Long Tran-Thanh, Rohit Singh, Fei Fang:
Designing the Game to Play: Optimizing Payoff Structure in Security Games. CoRR abs/1805.01987 (2018) - [i6]Chun Kai Ling, Fei Fang, J. Zico Kolter:
What game are we playing? End-to-end learning in normal and extensive form games. CoRR abs/1805.02777 (2018) - [i5]Swaminathan Gurumurthy, Lantao Yu, Chenyan Zhang, Yongchao Jin, Weiping Li, Haidong Zhang, Fei Fang:
Exploiting Data and Human Knowledge for Predicting Wildlife Poaching. CoRR abs/1805.05356 (2018) - [i4]Aaron M. Roth, Umang Bhatt, Tamara Amin, Afsaneh Doryab, Fei Fang, Manuela M. Veloso:
The Impact of Humanoid Affect Expression on Human Behavior in a Game-Theoretic Setting. CoRR abs/1806.03671 (2018) - [i3]Yufei Wang, Zheyuan Ryan Shi, Lantao Yu, Yi Wu, Rohit Singh, Lucas Joppa, Fei Fang:
Deep Reinforcement Learning for Green Security Games with Real-Time Information. CoRR abs/1811.02483 (2018) - [i2]Qingyu Guo, Jiarui Gan, Fei Fang, Long Tran-Thanh, Milind Tambe, Bo An:
On the Inducibility of Stackelberg Equilibrium for Security Games. CoRR abs/1811.03823 (2018) - 2017
- [j8]Fei Fang, Thanh Hong 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. AI Mag. 38(1): 23-36 (2017) - [j7]Nicole D. Sintov, Debarun Kar, Thanh Hong Nguyen, Fei Fang, Kevin Hoffman, Arnaud Lyet, Milind Tambe:
Keeping it Real: Using Real-World Problems to Teach AI to Diverse Audiences. AI Mag. 38(2): 35-47 (2017) - [j6]Jeannette Bohg, Xavier Boix, Nancy Chang, Elizabeth F. Churchill, Vivian Chu, Fei Fang, Jerome Feldman, Avelino J. Gonzalez, Takashi Kido, William F. Lawless, José L. Montaña, Santiago Ontañón, Jivko Sinapov, Donald A. Sofge, Luc Steels, Molly Wright Steenson, Keiki Takadama, Amulya Yadav:
Reports on the 2017 AAAI Spring Symposium Series. AI Mag. 38(4): 99-106 (2017) - [j5]Fei Fang, Thanh Hong Nguyen, Arunesh Sinha, Shahrzad Gholami, Andrew J. Plumptre, Lucas Joppa, Milind Tambe, Margaret Driciru, Fred Wanyama, Aggrey Rwetsiba, Rob Critchlow, Colin M. Beale:
Predicting poaching for wildlife Protection. IBM J. Res. Dev. 61(6): 3:1-3:12 (2017) - [c21]Zheyuan Shi, Fei Fang:
Optimizing Peer Teaching to Enhance Team Performance. AAMAS Workshops (Selected Papers) 2017: 138-150 - [c20]Debarun Kar, Benjamin J. Ford, Shahrzad Gholami, Fei Fang, Andrew J. Plumptre, Milind Tambe, Margaret Driciru, Fred Wanyama, Aggrey Rwetsiba, Mustapha Nsubaga, Joshua Mabonga:
Cloudy with a Chance of Poaching: Adversary Behavior Modeling and Forecasting with Real-World Poaching Data. AAMAS 2017: 159-167 - [c19]Elizabeth Bondi, Fei Fang, Debarun Kar, Venil Loyd Noronha, Donnabell Dmello, Milind Tambe, Arvind Iyer, Robert Hannaford:
VIOLA: Video Labeling Application for Security Domains. GameSec 2017: 377-396 - [c18]Haifeng Xu, Benjamin J. Ford, Fei Fang, Bistra Dilkina, Andrew J. Plumptre, Milind Tambe, Margaret Driciru, Fred Wanyama, Aggrey Rwetsiba, Mustapha Nsubaga, Joshua Mabonga:
Optimal Patrol Planning for Green Security Games with Black-Box Attackers. GameSec 2017: 458-477 - [c17]Shahrzad Gholami, Benjamin J. Ford, Fei Fang, Andrew J. Plumptre, Milind Tambe, Margaret Driciru, Fred Wanyama, Aggrey Rwetsiba, Mustapha Nsubaga, Joshua Mabonga:
Taking It for a Test Drive: A Hybrid Spatio-Temporal Model for Wildlife Poaching Prediction Evaluated Through a Controlled Field Test. ECML/PKDD (3) 2017: 292-304 - [e1]Stefan Rass, Bo An, Christopher Kiekintveld, Fei Fang, Stefan Schauer:
Decision and Game Theory for Security - 8th International Conference, GameSec 2017, Vienna, Austria, October 23-25, 2017, Proceedings. Lecture Notes in Computer Science 10575, Springer 2017, ISBN 978-3-319-68710-0 [contents] - [i1]Elizabeth Bondi, Debarun Kar, Venil Loyd Noronha, Donnabell Dmello, Milind Tambe, Fei Fang, Arvind Iyer, Robert Hannaford:
Video Labeling for Automatic Video Surveillance in Security Domains. CoRR abs/1710.08526 (2017) - 2016
- [j4]Debarun Kar, Fei Fang, Francesco Maria Delle Fave, Nicole D. Sintov, Milind Tambe, Arnaud Lyet:
Comparing human behavior models in repeated Stackelberg security games: An extended study. Artif. Intell. 240: 65-103 (2016) - [j3]Fei Fang, Thanh Hong Nguyen:
Green security games: apply game theory to addressing green security challenges. SIGecom Exch. 15(1): 78-83 (2016) - [c16]Fei Fang, Thanh Hong Nguyen, Rob Pickles, Wai Y. Lam, Gopalasamy R. Clements, Bo An, Amandeep Singh, Milind Tambe, Andrew Lemieux:
Deploying PAWS: Field Optimization of the Protection Assistant for Wildlife Security. AAAI 2016: 3966-3973 - [c15]Nicole D. Sintov, Debarun Kar, Thanh Hong Nguyen, Fei Fang, Kevin Hoffman, Arnaud Lyet, Milind Tambe:
From the Lab to the Classroom and Beyond: Extending a Game-Based Research Platform for Teaching AI to Diverse Audiences. AAAI 2016: 4107-4112 - [c14]Fei Fang, Thanh Hong Nguyen, Rob Pickles, Wai Y. Lam, Gopalasamy R. Clements, Bo An, Amandeep Singh, Milind Tambe:
Deploying PAWS to Combat Poaching: Game-Theoretic Patrolling in Areas with Complex Terrain (Demonstration). AAAI 2016: 4355-4356 - [c13]Anjon Basak, Fei Fang, Thanh Hong Nguyen, Christopher Kiekintveld:
Abstraction Methods for Solving Graph-Based Security Games. AAMAS Workshops (Visionary Papers) 2016: 13-33 - [c12]Anjon Basak, Fei Fang, Thanh Hong Nguyen, Christopher Kiekintveld:
Combining Graph Contraction and Strategy Generation for Green Security Games. GameSec 2016: 251-271 - [c11]Nika Haghtalab, Fei Fang, Thanh Hong Nguyen, Arunesh Sinha, Ariel D. Procaccia, Milind Tambe:
Three Strategies to Success: Learning Adversary Models in Security Games. IJCAI 2016: 308-314 - 2015
- [j2]Nitin Agarwal, Sean Andrist, Dan Bohus, Fei Fang, Laurie Fenstermacher, Lalana Kagal, Takashi Kido, Christopher Kiekintveld, William F. Lawless, Huan Liu, Andrew McCallum, Hemant Purohit, Oshani Seneviratne, Keiki Takadama, Gavin Taylor:
Reports on the 2015 AAAI Spring Symposium Series. AI Mag. 36(3): 113-119 (2015) - [c10]Debarun Kar, Fei Fang, Francesco Maria Delle Fave, Nicole D. Sintov, Milind Tambe, Arlette van Wissen:
Effectiveness of Probability Perception Modeling and Defender Strategy Generation Algorithms in Repeated Stackelberg Games: An Initial Report. AAAI Workshop: Computational Sustainability 2015 - [c9]Debarun Kar, Fei Fang, Francesco Maria Delle Fave, Nicole D. Sintov, Milind Tambe:
"A Game of Thrones": When Human Behavior Models Compete in Repeated Stackelberg Security Games. AAMAS 2015: 1381-1390 - [c8]Fei Fang, Peter Stone, Milind Tambe:
Defender Strategies In Domains Involving Frequent Adversary Interaction. AAMAS 2015: 1663-1664 - [c7]Fei Fang, Peter Stone, Milind Tambe:
When Security Games Go Green: Designing Defender Strategies to Prevent Poaching and Illegal Fishing. IJCAI 2015: 2589-2595 - 2014
- [c6]Haifeng Xu, Fei Fang, Albert Xin Jiang, Vincent Conitzer, Shaddin Dughmi, Milind Tambe:
Solving Zero-Sum Security Games in Discretized Spatio-Temporal Domains. AAAI 2014: 1500-1506 - [c5]William B. Haskell, Debarun Kar, Fei Fang, Milind Tambe, Sam Cheung, Elizabeth Denicola:
Robust Protection of Fisheries with COmPASS. AAAI 2014: 2978-2983 - 2013
- [j1]Fei Fang, Albert Xin Jiang, Milind Tambe:
Protecting Moving Targets with Multiple Mobile Resources. J. Artif. Intell. Res. 48: 583-634 (2013) - [c4]Fei Fang, Albert Xin Jiang, Milind Tambe:
Optimal patrol strategy for protecting moving targets with multiple mobile resources. AAMAS 2013: 957-964 - 2012
- [c3]Matthew Paul Johnson, Fei Fang, Milind Tambe:
Patrol Strategies to Maximize Pristine Forest Area. AAAI 2012: 295-301 - [c2]Matthew P. Johnson, Fei Fang, Rong Yang, Milind Tambe, Heidi J. Albers:
Challenges in Patrolling to Maximize Pristine Forest Area (Position Paper). AAAI Spring Symposium: Game Theory for Security, Sustainability, and Health 2012 - [c1]Rong Yang, Fei Fang, Albert Xin Jiang, Karthik Rajagopal, Milind Tambe, Rajiv T. Maheswaran:
Designing better strategies against human adversaries in network security games. AAMAS 2012: 1299-1300
Coauthor Index
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