Algebraic Markov Decision Processes. - Patrice Perny; Olivier Spanjaard; Paul Weng (IJCAI, 2005)

Qualitative Decision Making Under Possibilistic Uncertainty: Toward more Discriminating Criteria. - Paul Weng (UAI, 2005)

An Axiomatic Approach in Qualitative Decision Theory with Binary Possibilistic Utility. - Paul Weng (ECAI, 2006)

Axiomatic Foundations for a Class of Generalized Expected Utility: Algebraic Expected Utility. - Paul Weng (UAI, 2006)

Processus de décision markoviens et préférences non classiques. - Paul Weng (Rev. d'Intelligence Artif., 2006)

Conditions générales pour l'admissibilité de la programmation dynamique dans la décision séquentielle possibiliste. - Paul Weng (Rev. d'Intelligence Artif., 2007)

On Finding Compromise Solutions in Multiobjective Markov Decision Processes. - Patrice Perny; Paul Weng (ECAI, 2010)

Markov Decision Processes with Ordinal Rewards: Reference Point-Based Preferences. - Paul Weng (ICAPS, 2011)

Committee Selection with a Weight Constraint Based on a Pairwise Dominance Relation. - Charles Delort; Olivier Spanjaard; Paul Weng (ADT, 2011)

On Minimizing Ordered Weighted Regrets in Multiobjective Markov Decision Processes. - Wlodzimierz Ogryczak; Patrice Perny; Paul Weng (ADT, 2011)

Ordinal Decision Models for Markov Decision Processes. - Paul Weng (ECAI, 2012)

On WOWA Rank Reversal. - Wlodzimierz Ogryczak; Patrice Perny; Paul Weng (MDAI, 2012)

Approximation of Lorenz-Optimal Solutions in Multiobjective Markov Decision Processes. - Patrice Perny; Paul Weng; Judy Goldsmith; Josiah Hanna (AAAI (Late-Breaking Developments), 2013)

Top-k Selection based on Adaptive Sampling of Noisy Preferences. - Róbert Busa-Fekete; Balázs Szörényi; Weiwei Cheng; Paul Weng; Eyke Hüllermeier (ICML (3), 2013)

Interactive Value Iteration for Markov Decision Processes with Unknown Rewards. - Paul Weng; Bruno Zanuttini (IJCAI, 2013)

Markov Decision Processes with Functional Rewards. - Olivier Spanjaard; Paul Weng (MIWAI, 2013)

Axiomatic Foundations of Generalized Qualitative Utility. - Paul Weng (MIWAI, 2013)

A Compromise Programming Approach to multiobjective Markov Decision Processes. - Wlodzimierz Ogryczak; Patrice Perny; Paul Weng (Int. J. Inf. Technol. Decis. Mak., 2013)

Preface. - Darius Braziunas; Markus Endres; Kristen Brent Venable; Paul Weng; Lirong Xia (MPREF@AAAI, 2014)

Solving Hidden-Semi-Markov-Mode Markov Decision Problems. - Emmanuel Hadoux; Aurélie Beynier; Paul Weng (SUM, 2014)

Preference-based reinforcement learning: evolutionary direct policy search using a preference-based racing algorithm. - Róbert Busa-Fekete; Balázs Szörényi; Paul Weng; Weiwei Cheng; Eyke Hüllermeier (Mach. Learn., 2014)

Reducing the Number of Queries in Interactive Value Iteration. - Hugo Gilbert; Olivier Spanjaard; Paolo Viappiani; Paul Weng (ADT, 2015)

Qualitative Multi-Armed Bandits: A Quantile-Based Approach. - Balázs Szörényi; Róbert Busa-Fekete; Paul Weng; Eyke Hüllermeier (ICML, 2015)

Solving MDPs with Skew Symmetric Bilinear Utility Functions. - Hugo Gilbert; Olivier Spanjaard; Paolo Viappiani; Paul Weng (IJCAI, 2015)

Optimization of Probabilistic Argumentation with Markov Decision Models. - Emmanuel Hadoux; Aurélie Beynier; Nicolas Maudet; Paul Weng; Anthony Hunter (IJCAI, 2015)

Reports of the AAAI 2014 Conference Workshops. - Stefano V. Albrecht; André da Motta Salles Barreto; Darius Braziunas; David L. Buckeridge; Heriberto Cuayáhuitl; Nina Dethlefs; Markus Endres; Amir-massoud Farahmand; Mark Fox; Lutz Frommberger; Sam Ganzfried; Yolanda Gil; et al. (AI Mag., 2015)

Finding Risk-Averse Shortest Path with Time-Dependent Stochastic Costs. - Dajian Li; Paul Weng; Orkun Karabasoglu (MIWAI, 2016)

From Preference-Based to Multiobjective Sequential Decision-Making. - Paul Weng (MIWAI, 2016)

Model-Free Reinforcement Learning with Skew-Symmetric Bilinear Utilities. - Hugo Gilbert; Bruno Zanuttini; Paul Weng; Paolo Viappiani; Esther Nicart (UAI, 2016)

Quantile Reinforcement Learning. - Hugo Gilbert; Paul Weng (CoRR, 2016)

Optimizing Quantiles in Preference-Based Markov Decision Processes. - Hugo Gilbert; Paul Weng; Yan Xu (AAAI, 2017)

An Efficient Primal-Dual Algorithm for Fair Combinatorial Optimization Problems. - Viet Hung Nguyen; Paul Weng (COCOA (1), 2017)

Multi-objective Bandits: Optimizing the Generalized Gini Index. - Róbert Busa-Fekete; Balázs Szörényi; Paul Weng; Shie Mannor (ICML, 2017)

Optimal Threshold Policies for Robust Data Center Control. - Paul Weng; Zeqi Qiu; John A. W. B. Costanzo; Xiaoqi Yin; Bruno Sinopoli (CoRR, 2017)

Functional Reward Markov Decision Processes: Theory and Applications. - Paul Weng; Olivier Spanjaard (Int. J. Artif. Intell. Tools, 2017)

Adversarial Training Model Unifying Feature Driven and Point Process Perspectives for Event Popularity Prediction. - Qitian Wu; Chaoqi Yang; Hengrui Zhang; Xiaofeng Gao 001; Paul Weng; Guihai Chen (CIKM, 2018)

Mediation of Debates with Dynamic Argumentative Behaviors. - Emmanuel Hadoux; Aurélie Beynier; Nicolas Maudet; Paul Weng (COMMA, 2018)

Representing Relative Visual Attributes with a Reference-Point-Based Decision Model. - Marc T. Law; Paul Weng (ICPR, 2018)

Hierarchical Electric Vehicle Charging Aggregator Strategy Using Dantzig-Wolfe Decomposition. - M. Hadi Amini; Paul McNamara; Paul Weng; Orkun Karabasoglu; Yinliang Xu (IEEE Des. Test, 2018)

An efficient reinforcement learning algorithm for learning deterministic policies in continuous domains. - Matthieu Zimmer; Paul Weng (DAI, 2019)

Exploiting the Sign of the Advantage Function to Learn Deterministic Policies in Continuous Domains. - Matthieu Zimmer; Paul Weng (IJCAI, 2019)

Dual Sequential Prediction Models Linking Sequential Recommendation and Information Dissemination. - Qitian Wu; Yirui Gao; Xiaofeng Gao 001; Paul Weng; Guihai Chen (KDD, 2019)

Dual Graph Attention Networks for Deep Latent Representation of Multifaceted Social Effects in Recommender Systems. - Qitian Wu; Hengrui Zhang; Xiaofeng Gao 001; Peng He; Paul Weng; Han Gao; Guihai Chen (WWW, 2019)

Fairness in Reinforcement Learning. - Paul Weng (CoRR, 2019)

Invariant Transform Experience Replay. - Yijiong Lin; Jiancong Huang; Matthieu Zimmer; Juan Rojas 001; Paul Weng (CoRR, 2019)

Towards More Sample Efficiency in Reinforcement Learning with Data Augmentation. - Yijiong Lin; Jiancong Huang; Matthieu Zimmer; Juan Rojas 001; Paul Weng (CoRR, 2019)

Reinforcement Learning. - Olivier Buffet; Olivier Pietquin; Paul Weng (A Guided Tour of Artificial Intelligence Research (1) (I), 2020)

Decomposed Deep Reinforcement Learning for Robotic Control. - Yinzhao Dong; Chao Yu 004; Paul Weng; Ahmed Maustafa; Hui Cheng; Hongwei Ge (AAMAS, 2020)

Learning Fair Policies in Multi-Objective (Deep) Reinforcement Learning with Average and Discounted Rewards. - Umer Siddique; Paul Weng; Matthieu Zimmer (ICML, 2020)

Reinforcement Learning. - Olivier Buffet; Olivier Pietquin; Paul Weng (CoRR, 2020)

Learning Fair Policies in Multiobjective (Deep) Reinforcement Learning with Average and Discounted Rewards. - Umer Siddique; Paul Weng; Matthieu Zimmer (CoRR, 2020)

Learning Fair Policies in Decentralized Cooperative Multi-Agent Reinforcement Learning. - Matthieu Zimmer; Umer Siddique; Paul Weng (CoRR, 2020)

Invariant Transform Experience Replay: Data Augmentation for Deep Reinforcement Learning. - Yijiong Lin; Jiancong Huang; Matthieu Zimmer; Yisheng Guan; Juan Rojas 001; Paul Weng (IEEE Robotics Autom. Lett., 2020)

Safe Distributional Reinforcement Learning. - Jianyi Zhang; Paul Weng (DAI, 2021)

Learning Fair Policies in Decentralized Cooperative Multi-Agent Reinforcement Learning. - Matthieu Zimmer; Claire Glanois; Umer Siddique; Paul Weng (ICML, 2021)

Improving Generalization of Deep Reinforcement Learning-based TSP Solvers. - Wenbin Ouyang; Yisen Wang 001; Shaochen Han; Zhejian Jin; Paul Weng (SSCI, 2021)

Learning Symbolic Rules for Interpretable Deep Reinforcement Learning. - Zhihao Ma; Yuzheng Zhuang; Paul Weng; Hankz Hankui Zhuo; Dong Li 016; Wulong Liu; Jianye Hao (CoRR, 2021)

Neuro-Symbolic Hierarchical Rule Induction. - Claire Glanois; Xuening Feng; Zhaohui Jiang; Paul Weng; Matthieu Zimmer; Dong Li 016; Wulong Liu (CoRR, 2021)

Hyperparameter Auto-Tuning in Self-Supervised Robotic Learning. - Jiancong Huang; Juan Rojas 001; Matthieu Zimmer; Hongmin Wu; Yisheng Guan; Paul Weng (IEEE Robotics Autom. Lett., 2021)

CVaR-Regret Bounds for Multi-armed Bandits. - Chenmien Tan; Paul Weng (ACML, 2022)

Solving Complex Manipulation Tasks with Model-Assisted Model-Free Reinforcement Learning. - Jianshu Hu; Paul Weng (CoRL, 2022)

Planning with Q-Values in Sparse Reward Reinforcement Learning. - Hejun Lei; Paul Weng; Juan Rojas 001; Yisheng Guan (ICIRA (1), 2022)

Neuro-Symbolic Hierarchical Rule Induction. - Claire Glanois; Zhaohui Jiang; Xuening Feng; Paul Weng; Matthieu Zimmer; Dong Li 016; Wulong Liu; Jianye Hao (ICML, 2022)

A comparative study of linearization methods for Ordered Weighted Average. - Thi Quynh Trang Vo; Mourad Baïou; Viet Hung Nguyen; Paul Weng (RNDM, 2022)

Learning Rewards to Optimize Global Performance Metrics in Deep Reinforcement Learning. - Junqi Qian; Paul Weng; Chenmien Tan (AAMAS, 2023)

Fair Deep Reinforcement Learning with Generalized Gini Welfare Functions. - Guanbao Yu; Umer Siddique; Paul Weng (AAMAS Workshops, 2023)

Fair Deep Reinforcement Learning with Preferential Treatment. - Guanbao Yu; Umer Siddique; Paul Weng (ECAI, 2023)

Improving Subtour Elimination Constraint Generation in Branch-and-Cut Algorithms for the TSP with Machine Learning. - Thi Quynh Trang Vo; Mourad Baïou; Viet Hung Nguyen; Paul Weng (LION, 2023)

Unsupervised Salient Patch Selection for Data-Efficient Reinforcement Learning. - Zhaohui Jiang; Paul Weng (ECML/PKDD (4), 2023)

Analytics and machine learning in vehicle routing research. - Ruibin Bai; Xinan Chen; Zhi-Long Chen; Tianxiang Cui; Shuhui Gong; Wentao He; Xiaoping Jiang; Huan Jin; Jiahuan Jin; Graham Kendall; Jiawei Li 001; Zheng Lu 002; et al. (Int. J. Prod. Res., 2023)

Differentiable Logic Machines. - Matthieu Zimmer; Xuening Feng; Claire Glanois; Zhaohui Jiang; Jianyi Zhang; Paul Weng; Dong Li 016; Jianye Hao; Wulong Liu (Trans. Mach. Learn. Res., 2023)

Revisiting Data Augmentation in Deep Reinforcement Learning. - Jianshu Hu; Yunpeng Jiang; Paul Weng (ICLR, 2024)

INViT: A Generalizable Routing Problem Solver with Invariant Nested View Transformer. - Han Fang; Zhihao Song; Paul Weng; Yutong Ban (ICML, 2024)

Enhancing Class Fairness in Classification with A Two-Player Game Approach. - Yunpeng Jiang; Paul Weng; Yutong Ban (CoRR, 2024)

Imitation Learning from Suboptimal Demonstrations via Meta-Learning An Action Ranker. - Jiangdong Fan; Hongcai He; Paul Weng; Hui Xu; Jie Shao (CoRR, 2024)

Generalization in Deep RL for TSP Problems via Equivariance and Local Search. - Wenbin Ouyang; Yisen Wang 001; Paul Weng; Shaochen Han (SN Comput. Sci., 2024)

A survey on interpretable reinforcement learning. - Claire Glanois; Paul Weng; Matthieu Zimmer; Dong Li 016; Tianpei Yang; Jianye Hao; Wulong Liu (Mach. Learn., 2024)

Enhancing Online Reinforcement Learning with Meta-Learned Objective from Offline Data. - Shilong Deng; Zetao Zheng; Hongcai He; Paul Weng; Jie Shao 001 (AAAI, 2025)

DUO: Diverse, Uncertain, On-Policy Query Generation and Selection for Reinforcement Learning from Human Feedback. - Xuening Feng; Zhaohui Jiang; Timo Kaufmann; Puchen Xu; Eyke Hüllermeier; Paul Weng; Yifei Zhu (AAAI, 2025)

Reinforcement Learning from Imperfect Corrective Actions and Proxy Rewards. - Zhaohui Jiang; Xuening Feng; Paul Weng; Yifei Zhu; Yan Song; Tianze Zhou; Yujing Hu; Tangjie Lv; Changjie Fan (ICLR, 2025)

Understanding and Reducing the Class-Dependent Effects of Data Augmentation with A Two-Player Game Approach. - Yunpeng Jiang; Yutong Ban; Paul Weng (Trans. Mach. Learn. Res., 2025)

A Survey of Reinforcement Learning from Human Feedback. - Timo Kaufmann; Paul Weng; Viktor Bengs; Eyke Hüllermeier (Trans. Mach. Learn. Res., 2025)

ASAP: Learning Generalizable Online Bin Packing via Adaptive Selection After Pruning. - Han Fang; Paul Weng; Yutong Ban (CoRR, 2025)

State-novelty guided action persistence in deep reinforcement learning. - Jianshu Hu; Paul Weng; Yutong Ban (Mach. Learn., 2025)

Time Reversal Symmetry for Efficient Robotic Manipulations in Deep Reinforcement Learning. - Yunpeng Jiang; Jianshu Hu; Paul Weng; Yutong Ban (CoRR, 2025)

From fair solutions to compromise solutions in multi-objective deep reinforcement learning. - Junqi Qian; Umer Siddique; Guanbao Yu; Paul Weng (Neural Comput. Appl., 2025)