no code implementations • 18 May 2022 • Fei Fang, Kunal Sinha, Noah D. Goodman, Christopher Potts, Elisa Kreiss
It seems likely that these patterns are shaped by the environment a speaker is exposed to in complex ways.
1 code implementation • 11 May 2022 • Lily Xu, Arpita Biswas, Fei Fang, Milind Tambe
Preventing poaching through ranger patrols protects endangered wildlife, directly contributing to the UN Sustainable Development Goal 15 of life on land.
no code implementations • 30 Mar 2022 • Guan Yang, Minghuan Liu, Weijun Hong, Weinan Zhang, Fei Fang, Guangjun Zeng, Yue Lin
To this end, we characterize card and game features for DouDizhu to represent the perfect and imperfect information.
no code implementations • 19 Feb 2022 • Peide Huang, Mengdi Xu, Fei Fang, Ding Zhao
In this paper, we introduce a novel hierarchical formulation of robust RL - a general-sum Stackelberg game model called RRL-Stack - to formalize the sequential nature and provide extra flexibility for robust training.
no code implementations • 17 Feb 2022 • Stephanie Milani, Nicholay Topin, Manuela Veloso, Fei Fang
In this survey, we propose a novel taxonomy for organizing the XRL literature that prioritizes the RL setting.
no code implementations • 4 Oct 2021 • Hoon Oh, Yanhan Tang, Zong Zhang, Alexandre Jacquillat, Fei Fang
Unlike commercial ridesharing, non-commercial peer-to-peer (P2P) ridesharing has been subject to limited research -- although it can promote viable solutions in non-urban communities.
1 code implementation • 21 Aug 2021 • Weizhe Chen, Zihan Zhou, Yi Wu, Fei Fang
One practical requirement in solving dynamic games is to ensure that the players play well from any decision point onward.
1 code implementation • 13 Aug 2021 • Steven Jecmen, Hanrui Zhang, Ryan Liu, Fei Fang, Vincent Conitzer, Nihar B. Shah
Many scientific conferences employ a two-phase paper review process, where some papers are assigned additional reviewers after the initial reviews are submitted.
1 code implementation • 15 Jun 2021 • Lily Xu, Andrew Perrault, Fei Fang, Haipeng Chen, Milind Tambe
We formulate the problem as a game between the defender and nature who controls the parameter values of the adversarial behavior and design an algorithm MIRROR to find a robust policy.
2 code implementations • ICLR 2021 • Zhenggang Tang, Chao Yu, Boyuan Chen, Huazhe Xu, Xiaolong Wang, Fei Fang, Simon Du, Yu Wang, Yi Wu
We propose a simple, general and effective technique, Reward Randomization for discovering diverse strategic policies in complex multi-agent games.
no code implementations • 25 Feb 2021 • Nicholay Topin, Stephanie Milani, Fei Fang, Manuela Veloso
Because of this decision tree equivalence, any function approximator can be used during training, including a neural network, while yielding a decision tree policy for the base MDP.
1 code implementation • NeurIPS 2020 • Chun Kai Ling, Fei Fang, J. Zico Kolter
A central problem in machine learning and statistics is to model joint densities of random variables from data.
2 code implementations • 14 Sep 2020 • Lily Xu, Elizabeth Bondi, Fei Fang, Andrew Perrault, Kai Wang, Milind Tambe
Conservation efforts in green security domains to protect wildlife and forests are constrained by the limited availability of defenders (i. e., patrollers), who must patrol vast areas to protect from attackers (e. g., poachers or illegal loggers).
1 code implementation • 26 Aug 2020 • Zheyuan Ryan Shi, Zhiwei Steven Wu, Rayid Ghani, Fei Fang
In this paper, we introduce bandit data-driven optimization, the first iterative prediction-prescription framework to address these pain points.
no code implementations • 5 Aug 2020 • Jingxing Jiang, Zhubin Wang, Fei Fang, Binqiang Zhao
Critical as is to improve the online shopping experience for customers and merchants, how to find a proper approach for user intent prediction are paid great attention in both industry and academia.
2 code implementations • NeurIPS 2020 • Steven Jecmen, Hanrui Zhang, Ryan Liu, Nihar B. Shah, Vincent Conitzer, Fei Fang
We further consider the problem of restricting the joint probability that certain suspect pairs of reviewers are assigned to certain papers, and show that this problem is NP-hard for arbitrary constraints on these joint probabilities but efficiently solvable for a practical special case.
1 code implementation • ICLR 2020 • Qian Long, Zihan Zhou, Abhibav Gupta, Fei Fang, Yi Wu, Xiaolong Wang
In multi-agent games, the complexity of the environment can grow exponentially as the number of agents increases, so it is particularly challenging to learn good policies when the agent population is large.
no code implementations • 7 Jan 2020 • Zheyuan Ryan Shi, Claire Wang, Fei Fang
Artificial intelligence for social good (AI4SG) is a research theme that aims to use and advance artificial intelligence to address societal issues and improve the well-being of the world.
no code implementations • 16 Dec 2019 • Andrew Perrault, Fei Fang, Arunesh Sinha, Milind Tambe
With the maturing of AI and multiagent systems research, we have a tremendous opportunity to direct these advances towards addressing complex societal problems.
no code implementations • NeurIPS 2019 • Gabriele Farina, Chun Kai Ling, Fei Fang, Tuomas Sandholm
We show that a regret minimizer can be designed for a scaled extension of any two convex sets, and that from the decomposition we then obtain a global regret minimizer.
no code implementations • 10 Sep 2019 • Liheng Chen, Hongyi Guo, Yali Du, Fei Fang, Haifeng Zhang, Yaoming Zhu, Ming Zhou, Wei-Nan Zhang, Qing Wang, Yong Yu
Although existing works formulate this problem into a centralized learning with decentralized execution framework, which avoids the non-stationary problem in training, their decentralized execution paradigm limits the agents' capability to coordinate.
no code implementations • 20 Jul 2019 • Taoan Huang, Bohui Fang, Xiaohui Bei, Fei Fang
Transportation service providers that dispatch drivers and vehicles to riders start to support both on-demand ride requests posted in real time and rides scheduled in advance, leading to new challenges which, to the best of our knowledge, have not been addressed by existing works.
no code implementations • 13 May 2019 • Zheyuan Ryan Shi, Ariel D. Procaccia, Kevin S. Chan, Sridhar Venkatesan, Noam Ben-Asher, Nandi O. Leslie, Charles Kamhoua, Fei Fang
In order to formally reason about deception, we introduce the feature deception problem (FDP), a domain-independent model and present a learning and planning framework for finding the optimal deception strategy, taking into account the adversary's preferences which are initially unknown to the defender.
no code implementations • 11 Mar 2019 • Chun Kai Ling, Fei Fang, J. Zico Kolter
With the recent advances in solving large, zero-sum extensive form games, there is a growing interest in the inverse problem of inferring underlying game parameters given only access to agent actions.
no code implementations • 3 Jan 2019 • Zheyuan Ryan Shi, Aaron Schlenker, Brian Hay, Daniel Bittleston, Siyu Gao, Emily Peterson, John Trezza, Fei Fang
Cyber adversaries have increasingly leveraged social engineering attacks to breach large organizations and threaten the well-being of today's online users.
no code implementations • 6 Nov 2018 • Yufei Wang, Zheyuan Ryan Shi, Lantao Yu, Yi Wu, Rohit Singh, Lucas Joppa, Fei Fang
Green Security Games (GSGs) have been proposed and applied to optimize patrols conducted by law enforcement agencies in green security domains such as combating poaching, illegal logging and overfishing.
1 code implementation • 10 Jun 2018 • Aaron M. Roth, Umang Bhatt, Tamara Amin, Afsaneh Doryab, Fei Fang, Manuela Veloso
In this pilot study, we investigate (1) in what way a robot can express a certain mood to influence a human's decision making behavioral model; (2) how and to what extent the human will be influenced in a game theoretic setting.
1 code implementation • 7 May 2018 • Chun Kai Ling, Fei Fang, J. Zico Kolter
Although recent work in AI has made great progress in solving large, zero-sum, extensive-form games, the underlying assumption in most past work is that the parameters of the game itself are known to the agents.
no code implementations • 5 May 2018 • Zheyuan Ryan Shi, Ziye Tang, Long Tran-Thanh, Rohit Singh, Fei Fang
We study Stackelberg Security Games where the defender, in addition to allocating defensive resources to protect targets from the attacker, can strategically manipulate the attacker's payoff under budget constraints in weighted L^p-norm form regarding the amount of change.