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| 2024 | 30 Years of Engineering Multi-Agent Systems: What and Why? Michael Winikoff |
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| 2024 | A Distributed Approach for Fault Detection in Swarms of Robots. Alessandro Carminati, Davide Azzalini, Simone Vantini, Francesco Amigoni |
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| 2024 | A Multiagent Path Search Algorithm for Large-Scale Coalition Structure Generation. Redha Taguelmimt, Samir Aknine, Djamila Boukredera, Narayan Changder, Tuomas Sandholm |
| 2024 | A Negotiator's Backup Plan: Optimal Concessions with a Reservation Value. Tamara C. P. Florijn, Pinar Yolum, Tim Baarslag |
| 2024 | A Reinforcement Learning Framework for Studying Group and Individual Fairness. Alexandra Cimpean, Catholijn M. Jonker, Pieter Libin, Ann Nowé |
| 2024 | A SAT-based Approach for Argumentation Dynamics. Jean-Marie Lagniez, Emmanuel Lonca, Jean-Guy Mailly |
| 2024 | A Simple 1.5-approximation Algorithm for a Wide Range of Maximum Size Stable Matching Problems. Gergely Csáji |
| 2024 | A Summary of Online Markov Decision Processes with Non-oblivious Strategic Adversary. Le Cong Dinh, David Henry Mguni, Long Tran-Thanh, Jun Wang, Yaodong Yang |
| 2024 | A Summary of the RGS Cyrille Berger, Patrick Doherty, Piotr Rudol, Mariusz Wzorek |
| 2024 | A Survey of Multi-Agent Deep Reinforcement Learning with Communication. Changxi Zhu, Mehdi Dastani, Shihan Wang |
| 2024 | A Symbolic Sequential Equilibria Solver for Game Theory Explorer. Moritz Graf, Thorsten Engesser, Bernhard Nebel |
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| 2024 | A Trajectory Perspective on the Role of Data Sampling Techniques in Offline Reinforcement Learning. Jinyi Liu, Yi Ma, Jianye Hao, Yujing Hu, Yan Zheng, Tangjie Lv, Changjie Fan |
| 2024 | ANOTO: Improving Automated Negotiation via Offline-to-Online Reinforcement Learning. Siqi Chen, Jianing Zhao, Kai Zhao, Gerhard Weiss, Fengyun Zhang, Ran Su, Yang Dong, Daqian Li, Kaiyou Lei |
| 2024 | Abstracting Assumptions in Structured Argumentation. Iosif Apostolakis, Zeynep G. Saribatur, Johannes P. Wallner |
| 2024 | Abstraction in Non-Monotonic Reasoning. Iosif Apostolakis |
| 2024 | Act as You Learn: Adaptive Decision-Making in Non-Stationary Markov Decision Processes. Baiting Luo, Yunuo Zhang, Abhishek Dubey, Ayan Mukhopadhyay |
| 2024 | Actual Trust in Multiagent Systems. Michael Akintunde, Vahid Yazdanpanah, Asieh Salehi Fathabadi, Corina Cîrstea, Mehdi Dastani, Luc Moreau |
| 2024 | Adaptive Decision-Making in Non-Stationary Markov Decision Processes. Baiting Luo |
| 2024 | Adaptive Discounting of Training Time Attacks. Ridhima Bector, Abhay Aradhya, Chai Quek, Zinovi Rabinovich |
| 2024 | Adaptive Evolutionary Reinforcement Learning Algorithm with Early Termination Strategy. Xiaoqiang Wu, Qingling Zhu, Qiuzhen Lin, Weineng Chen, Jianqiang Li |
| 2024 | Adaptive Incentive Engineering in Citizen-Centric AI. Behrad Koohy, Jan Buermann, Vahid Yazdanpanah, Pamela Briggs, Paul Pschierer-Barnfather, Enrico H. Gerding, Sebastian Stein |
| 2024 | Adaptive Primal-Dual Method for Safe Reinforcement Learning. Weiqin Chen, James Onyejizu, Long Vu, Lan Hoang, Dharmashankar Subramanian, Koushik Kar, Sandipan Mishra, Santiago Paternain |
| 2024 | Addressing Permutation Challenges in Multi-Agent Reinforcement Learning. Somnath Hazra, Pallab Dasgupta, Soumyajit Dey |
| 2024 | Advancing Sample Efficiency and Explainability in Multi-Agent Reinforcement Learning. Zhicheng Zhang |
| 2024 | Agent-Based Triangle Counting and Its Applications in Anonymous Graphs. Prabhat Kumar Chand, Apurba Das, Anisur Rahaman Molla |
| 2024 | Agents and Humans: Trajectories and Perspectives. Liz Sonenberg |
| 2024 | Aleatoric Predicates: Reasoning about Marbles. Tim French |
| 2024 | Algorithmic Filtering, Out-Group Stereotype, and Polarization on Social Media. Jean Springsteen, William Yeoh, Dino P. Christenson |
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| 2024 | Allocating Contiguous Blocks of Indivisible Chores Fairly: Revisited. Ankang Sun, Bo Li |
| 2024 | Allocating Resources with Imperfect Information. Shiji Xing |
| 2024 | An Online Learning Theory of Brokerage. Natasa Bolic, Tommaso Cesari, Roberto Colomboni |
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| 2024 | Anytime Multi-Agent Path Finding using Operation Parallelism in Large Neighborhood Search. Shao-Hung Chan, Zhe Chen, Dian-Lun Lin, Yue Zhang, Daniel Harabor, Sven Koenig, Tsung-Wei Huang, Thomy Phan |
| 2024 | Applying Opponent Modeling for Automatic Bidding in Online Repeated Auctions. Yudong Hu, Congying Han, Tiande Guo, Hao Xiao |
| 2024 | Approximately Fair Allocation of Indivisible Items with Random Valuations. Alessandro Aloisio, Vittorio Bilò, Antonio Mario Caruso, Michele Flammini, Cosimo Vinci |
| 2024 | Approximating APS Under Submodular and XOS Valuations with Binary Marginals. Pooja Kulkarni, Rucha Kulkarni, Ruta Mehta |
| 2024 | Approximating the Core via Iterative Coalition Sampling. Ian Gemp, Marc Lanctot, Luke Marris, Yiran Mao, Edgar A. Duéñez-Guzmán, Sarah Perrin, András György, Romuald Elie, Georgios Piliouras, Michael Kaisers, Daniel Hennes, Kalesha Bullard, Kate Larson, Yoram Bachrach |
| 2024 | Assessing Fairness of Residential Dynamic Pricing for Electricity using Active Learning with Agent-based Simulation. Swapna Thorve, Henning S. Mortveit, Anil Vullikanti, Madhav V. Marathe, Samarth Swarup |
| 2024 | Atlas-X Equity Financing: Unlocking New Methods to Securely Obfuscate Axe Inventory Data Based on Differential Privacy. Antigoni Polychroniadou, Gabriele Cipriani, Richard Hua, Tucker Balch |
| 2024 | Attacking Multi-Player Bandits and How to Robustify Them. Shivakumar Mahesh, Anshuka Rangi, Haifeng Xu, Long Tran-Thanh |
| 2024 | Attention Graph for Multi-Robot Social Navigation with Deep Reinforcement Learning. Erwan Escudie, Laëtitia Matignon, Jacques Saraydaryan |
| 2024 | Attention-based Priority Learning for Limited Time Multi-Agent Path Finding. Yibin Yang, Mingfeng Fan, Chengyang He, Jianqiang Wang, Heye Huang, Guillaume Sartoretti |
| 2024 | Attila: A Negotiating Agent for the Game of Diplomacy, Based on Purely Symbolic A.I. Dave de Jonge, Laura Rodriguez Cima |
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| 2024 | Autonomous Skill Acquisition for Robots Using Graduated Learning. Gautham Vasan |
| 2024 | BAR Nash Equilibrium and Application to Blockchain Design. Maxime Reynouard, Olga Gorelkina, Rida Laraki |
| 2024 | BDI Agents in Natural Language Environments. Alexandre Yukio Ichida, Felipe Meneguzzi, Rafael C. Cardoso |
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| 2024 | Banzhaf Power in Hierarchical Games. John Randolph, Amy Greenwald, Denizalp Goktas |
| 2024 | Battlefield Transfers in Coalitional Blotto Games. Vade Shah, Jason R. Marden |
| 2024 | Bayesian Behavioural Model Estimation for Live Crowd Simulation. Fumiyasu Makinoshima, Tetsuro Takahashi, Yusuke Oishi |
| 2024 | Bayesian Ensembles for Exploration in Deep Q-Learning. Pascal R. van der Vaart, Neil Yorke-Smith, Matthijs T. J. Spaan |
| 2024 | Bayesian Model-Free Deep Reinforcement Learning. Pascal R. van der Vaart |
| 2024 | Behaviour Modelling of Social Animals via Causal Structure Discovery and Graph Neural Networks. Gaël Gendron, Yang Chen, Mitchell Rogers, Yiping Liu, Mihailo Azhar, Shahrokh Heidari, David Arturo Soriano Valdez, Kobe Knowles, Padriac O'Leary, Simon Eyre, Michael Witbrock, Gillian Dobbie, Jiamou Liu, Patrice Delmas |
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| 2024 | Bellman Momentum on Deep Reinforcement Learning. Huihui Zhang |
| 2024 | Benchmarking MARL on Long Horizon Sequential Multi-Objective Tasks. Minghong Geng, Shubham Pateria, Budhitama Subagdja, Ah-Hwee Tan |
| 2024 | Beyond Surprise: Improving Exploration Through Surprise Novelty. Hung Le, Kien Do, Dung Nguyen, Svetha Venkatesh |
| 2024 | Boosting Continuous Control with Consistency Policy. Yuhui Chen, Haoran Li, Dongbin Zhao |
| 2024 | Boosting Studies of Multi-Agent Reinforcement Learning on Google Research Football Environment: The Past, Present, and Future. Yan Song, He Jiang, Haifeng Zhang, Zheng Tian, Weinan Zhang, Jun Wang |
| 2024 | Bootstrapped Policy Learning: Goal Shaping for Efficient Task-oriented Dialogue Policy Learning. Yangyang Zhao, Mehdi Dastani, Shihan Wang |
| 2024 | Bootstrapping Linear Models for Fast Online Adaptation in Human-Agent Collaboration. Benjamin A. Newman, Christopher Jason Paxton, Kris Kitani, Henny Admoni |
| 2024 | Bounding Consideration Probabilities in Consider-Then-Choose Ranking Models. Ben Aoki-Sherwood, Catherine Bregou, David Liben-Nowell, Kiran Tomlinson, Thomas Zeng |
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| 2024 | BrainSLAM: SLAM on Neural Population Activity Data. Kipp McAdam Freud, Nathan F. Lepora, Matt W. Jones, Cian O'Donnell |
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| 2024 | Building Trustworthy Human-Centric Autonomous Systems Via Explanations. Balint Gyevnar |
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| 2024 | Can Poverty Be Reduced by Acting on Discrimination? An Agent-based Model for Policy Making. Alba Aguilera, Nieves Montes, Georgina Curto, Carles Sierra, Nardine Osman |
| 2024 | Capacity Modification in the Stable Matching Problem. Salil Gokhale, Samarth Singla, Shivika Narang, Rohit Vaish |
| 2024 | Catfished! Impacts of Strategic Misrepresentation in Online Dating. Oz Kilic, Alan Tsang |
| 2024 | Causal Explanations for Sequential Decision-Making in Multi-Agent Systems. Balint Gyevnar, Cheng Wang, Christopher G. Lucas, Shay B. Cohen, Stefano V. Albrecht |
| 2024 | Centralized Training with Hybrid Execution in Multi-Agent Reinforcement Learning. Pedro P. Santos, Diogo S. Carvalho, Miguel Vasco, Alberto Sardinha, Pedro A. Santos, Ana Paiva, Francisco S. Melo |
| 2024 | Charging Electric Vehicles Fairly and Efficiently. Ramsundar Anandanarayanan, Swaprava Nath, Rohit Vaish |
| 2024 | Clique Analysis and Bypassing in Continuous-Time Conflict-Based Search. Thayne T. Walker, Nathan R. Sturtevant, Ariel Felner |
| 2024 | Coalition Formation with Bounded Coalition Size. Chaya Levinger, Noam Hazon, Sofia Simola, Amos Azaria |
| 2024 | Cognizing and Imitating Robotic Skills via a Dual Cognition-Action Architecture. Zixuan Chen, Ze Ji, Shuyang Liu, Jing Huo, Yiyu Chen, Yang Gao |
| 2024 | Collaborative Deep Reinforcement Learning for Solving Multi-Objective Vehicle Routing Problems. Yaoxin Wu, Mingfeng Fan, Zhiguang Cao, Ruobin Gao, Yaqing Hou, Guillaume Sartoretti |
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| 2024 | Combinatorial Client-Master Multiagent Deep Reinforcement Learning for Task Offloading in Mobile Edge Computing. Zemuy Tesfay Gebrekidan, Sebastian Stein, Timothy J. Norman |
| 2024 | Combining Theory of Mind and Abductive Reasoning in Agent-Oriented Programming. Nieves Montes, Michael Luck, Nardine Osman, Odinaldo Rodrigues, Carles Sierra |
| 2024 | Combining Voting and Abstract Argumentation to Understand Online Discussions. Michael Bernreiter, Jan Maly, Oliviero Nardi, Stefan Woltran |
| 2024 | Communication and Generalization in Multi-Agent Learning. Jiaxun Cui |
| 2024 | Competitive Analysis of Online Facility Open Problem. Binghan Wu, Wei Bao, Bing Zhou |
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| 2024 | Computing Balanced Solutions for Large International Kidney Exchange Schemes when Cycle Length is Unbounded. Márton Benedek, Péter Biró, Gergely Csáji, Matthew Johnson, Daniël Paulusma, Xin Ye |
| 2024 | Computing Nash Equilibria in Multidimensional Congestion Games. Mohammad T. Irfan, Hau Chan, Jared Soundy |
| 2024 | Computing Optimal Commitments to Strategies and Outcome-Conditional Utility Transfers. Nathaniel Sauerberg, Caspar Oesterheld |
| 2024 | Concurrency Model of BDI Programming Frameworks: Why Should We Control It? Martina Baiardi, Samuele Burattini, Giovanni Ciatto, Danilo Pianini, Andrea Omicini, Alessandro Ricci |
| 2024 | Confidence-Based Curriculum Learning for Multi-Agent Path Finding. Thomy Phan, Joseph Driscoll, Justin Romberg, Sven Koenig |
| 2024 | Consensus of Nonlinear Multi-Agent Systems with Semi-Markov Switching Under DoS Attacks. Sheng Tian, Hong Shen, Yuan Tian, Hui Tian |
| 2024 | Containing the Spread of a Contagion on a Tree. Michela Meister, Jon M. Kleinberg |
| 2024 | Context-aware Communication for Multi-agent Reinforcement Learning. Xinran Li, Jun Zhang |
| 2024 | Contiguous Allocation of Binary Valued Indivisible Items on a Path. Yasushi Kawase, Bodhayan Roy, Mohammad Azharuddin Sanpui |
| 2024 | Continual Depth-limited Responses for Computing Counter-strategies in Sequential Games. David Milec, Ondrej Kubícek, Viliam Lisý |
| 2024 | Continual Optimistic Initialization for Value-Based Reinforcement Learning. Sheelabhadra Dey, James Ault, Guni Sharon |
| 2024 | Continuous Monte Carlo Graph Search. Kalle Kujanpää, Amin Babadi, Yi Zhao, Juho Kannala, Alexander Ilin, Joni Pajarinen |
| 2024 | Controlling Delegations in Liquid Democracy. Shiri Alouf-Heffetz, Tanmay Inamdar, Pallavi Jain, Nimrod Talmon, Yash More Hiren |
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| 2024 | Cooperation and Coordination in Heterogeneous Populations with Interaction Diversity. Hao Guo, Zhen Wang, Junliang Xing, Pin Tao, Yuanchun Shi |
| 2024 | Cooperative Electric Vehicles Planning. Jaël Champagne Gareau, Marc-André Lavoie, Guillaume Gosset, Éric Beaudry |
| 2024 | Cooperative Multi-Agent Reinforcement Learning in Convention Reliant Environments. Jarrod Shipton |
| 2024 | Cost-aware Offline Safe Meta Reinforcement Learning with Robust In-Distribution Online Task Adaptation. Cong Guan, Ruiqi Xue, Ziqian Zhang, Lihe Li, Yi-Chen Li, Lei Yuan, Yang Yu |
| 2024 | Cournot Queueing Games with Applications to Mobility Systems. Matthew Sheldon, Dario Paccagnan, Giuliano Casale |
| 2024 | Covert Planning aganist Imperfect Observers. Haoxiang Ma, Chongyang Shi, Shuo Han, Michael R. Dorothy, Jie Fu |
| 2024 | Cutsets and EF1 Fair Division of Graphs. Jiehua Chen, William S. Zwicker |
| 2024 | DCT: Dual Channel Training of Action Embeddings for Reinforcement Learning with Large Discrete Action Spaces. Pranavi Pathakota, Hardik Meisheri, Harshad Khadilkar |
| 2024 | Decent-BRM: Decentralization through Block Reward Mechanisms. Varul Srivastava, Sujit Gujar |
| 2024 | Decentralised Emergence of Robust and Adaptive Linguistic Conventions in Populations of Autonomous Agents Grounded in Continuous Worlds. Jérôme Botoko Ekila, Jens Nevens, Lara Verheyen, Katrien Beuls, Paul Van Eecke |
| 2024 | Decentralized Competing Bandits in Many-to-One Matching Markets. Yirui Zhang, Zhixuan Fang |
| 2024 | Decentralized Control of Distributed Manipulators: An Information Diffusion Approach. Nicolas Bessone, Payam Zahadat, Kasper Støy |
| 2024 | Decentralized Federated Policy Gradient with Byzantine Fault-Tolerance and Provably Fast Convergence. Philip Jordan, Florian Grötschla, Flint Xiaofeng Fan, Roger Wattenhofer |
| 2024 | Decentralized Safe Control for Multi-Robot Navigation in Dynamic Environments with Limited Sensing. Saad Khan, Mayank Baranwal, Srikant Sukumar |
| 2024 | Deceptive Path Planning via Reinforcement Learning with Graph Neural Networks. Michael Y. Fatemi, Wesley A. Suttle, Brian M. Sadler |
| 2024 | Decision Making in Non-Stationary Environments with Policy-Augmented Search. Ava Pettet, Yunuo Zhang, Baiting Luo, Kyle Hollins Wray, Hendrik Baier, Aron Laszka, Abhishek Dubey, Ayan Mukhopadhyay |
| 2024 | Decision Market Based Learning for Multi-agent Contextual Bandit Problems. Wenlong Wang, Thomas Pfeiffer |
| 2024 | Deep Anomaly Detection via Active Anomaly Search. Chao Chen, Dawei Wang, Feng Mao, Jiacheng Xu, Zongzhang Zhang, Yang Yu |
| 2024 | Deep Hawkes Process for High-Frequency Market Making. Pankaj Kumar |
| 2024 | Deep Learning for Population-Dependent Controls in Mean Field Control Problems with Common Noise. Gökçe Dayanikli, Mathieu Laurière, Jiacheng Zhang |
| 2024 | Deep Reinforcement Learning with Coalition Action Selection for Online Combinatorial Resource Allocation with Arbitrary Action Space. Zemuy Tesfay Gebrekidan, Sebastian Stein, Timothy J. Norman |
| 2024 | Defining Deception in Decision Making. Marwa Abdulhai, Micah Carroll, Justin Svegliato, Anca D. Dragan, Sergey Levine |
| 2024 | Design Patterns for Explainable Agents (XAg). Sebastian Rodriguez, John Thangarajah, Andrew Davey |
| 2024 | Designing Artificial Reasoners for Communication. Emiliano Lorini |
| 2024 | Designing Redistribution Mechanisms for Reducing Transaction Fees in Blockchains. Sankarshan Damle, Manisha Padala, Sujit Gujar |
| 2024 | Detecting Anomalous Agent Decision Sequences Based on Offline Imitation Learning. Chen Wang, Sarah M. Erfani, Tansu Alpcan, Christopher Leckie |
| 2024 | Developing a Multi-agent and Self-adaptive Framework with Deep Reinforcement Learning for Dynamic Portfolio Risk Management. Zhenglong Li, Vincent W. L. Tam, Kwan L. Yeung |
| 2024 | Difference of Convex Functions Programming for Policy Optimization in Reinforcement Learning. Akshat Kumar |
| 2024 | Discovering Consistent Subelections. Lukasz Janeczko, Jérôme Lang, Grzegorz Lisowski, Stanislaw Szufa |
| 2024 | Disentangling Policy from Offline Task Representation Learning via Adversarial Data Augmentation. Chengxing Jia, Fuxiang Zhang, Yi-Chen Li, Chenxiao Gao, Xu-Hui Liu, Lei Yuan, Zongzhang Zhang, Yang Yu |
| 2024 | Distance-Aware Attentive Framework for Multi-Agent Collaborative Perception in Presence of Pose Error. Binyu Zhao, Wei Zhang, Zhaonian Zou |
| 2024 | Distributed Online Rollout for Multivehicle Routing in Unmapped Environments. Jamison W. Weber, Dhanush R. Giriyan, Devendra R. Parkar, Dimitri P. Bertsekas, Andréa W. Richa |
| 2024 | Distribution of Chores with Information Asymmetry. Hadi Hosseini, Joshua Kavner, Tomasz Was, Lirong Xia |
| 2024 | Distributive and Temporal Fairness in Algorithmic Collective Decision-Making. Nicholas Teh |
| 2024 | DuaLight: Enhancing Traffic Signal Control by Leveraging Scenario-Specific and Scenario-Shared Knowledge. Jiaming Lu, Jingqing Ruan, Haoyuan Jiang, Ziyue Li, Hangyu Mao, Rui Zhao |
| 2024 | Dual Role AoI-based Incentive Mechanism for HD map Crowdsourcing. Wentao Ye, Bo Liu, Yuan Luo, Jianwei Huang |
| 2024 | Dual-Policy-Guided Offline Reinforcement Learning with Optimal Stopping. Weibo Jiang, Shaohui Li, Zhi Li, Yuxin Ke, Zhizhuo Jiang, Yaowen Li, Yu Liu |
| 2024 | Dynamic Epistemic Logic of Resource Bounded Information Mining Agents. Vitaliy Dolgorukov, Rustam Galimullin, Maksim Gladyshev |
| 2024 | ELA: Exploited Level Augmentation for Offline Learning in Zero-Sum Games. Shiqi Lei, Kanghoon Lee, Linjing Li, Jinkyoo Park, Jiachen Li |
| 2024 | ENOTO: Improving Offline-to-Online Reinforcement Learning with Q-Ensembles. Kai Zhao, Jianye Hao, Yi Ma, Jinyi Liu, Yan Zheng, Zhaopeng Meng |
| 2024 | EVtonomy: A Personalised Route Planner for Electric Vehicles. Alexandry Augustin, Elnaz Shafipour, Sebastian Stein |
| 2024 | Efficient Collaboration with Unknown Agents: Ignoring Similar Agents without Checking Similarity. Yansong Li, Shuo Han |
| 2024 | Efficient Continuous Space BeliefMDP Solutions for Navigation and Active Sensing. Himanshu Gupta |
| 2024 | Efficient Method for Finding Optimal Strategies in Chopstick Auctions with Uniform Objects Values. Stanislaw Kazmierowski, Marcin Dziubinski |
| 2024 | Efficient Public Health Intervention Planning Using Decomposition-Based Decision-focused Learning. Sanket Shah, Arun Suggala, Milind Tambe, Aparna Taneja |
| 2024 | Efficient Size-based Hybrid Algorithm for Optimal Coalition Structure Generation. Redha Taguelmimt, Samir Aknine, Djamila Boukredera, Narayan Changder, Tuomas Sandholm |
| 2024 | Electric Vehicle Routing for Emergency Power Supply with Deep Reinforcement Learning. Daisuke Kikuta, Hiroki Ikeuchi, Kengo Tajiri, Yuta Toyama, Masaki Nakamura, Yuusuke Nakano |
| 2024 | Embracing Relational Reasoning in Multi-Agent Actor-Critic. Sharlin Utke, Jeremie Houssineau, Giovanni Montana |
| 2024 | Emergence of Linguistic Conventions In Multi-Agent Systems Through Situated Communicative Interactions. Jérôme Botoko Ekila |
| 2024 | Emergent Cooperation under Uncertain Incentive Alignment. Nicole Orzan, Erman Acar, Davide Grossi, Roxana Radulescu |
| 2024 | Emergent Dominance Hierarchies in Reinforcement Learning Agents. Ram Rachum, Yonatan Nakar, Bill Tomlinson, Nitay Alon, Reuth Mirsky |
| 2024 | Empowering BDI Agents with Generalised Decision-Making. Ramon Fraga Pereira, Felipe Meneguzzi |
| 2024 | Enabling BDI Agents to Reason on a Dynamic Action Repertoire in Hypermedia Environments. Danai Vachtsevanou, Bruno de Lima, Andrei Ciortea, Jomi Fred Hübner, Simon Mayer, Jérémy Lemée |
| 2024 | End to End Camera only Drone Detection and Tracking Demo within a Multi-agent Framework with a CNN-LSTM Model for Range Estimation. Maxence de Rochechouart, Raed Abu Zitar, Amal El Fallah Seghrouchni, Frédéric Barbaresco |
| 2024 | Engaging the Elderly in Exercise with Agents: A Gamified Stationary Bike System for Sarcopenia Management. Yang Qiu, Ping Chen, Huiguo Zhang, Bo Huang, Di Wang, Zhiqi Shen |
| 2024 | Engineering LaCAM*: Towards Real-time, Large-scale, and Near-optimal Multi-agent Pathfinding. Keisuke Okumura |
| 2024 | Enhancing Search and Rescue Capabilities in Hazardous Communication-Denied Environments through Path-Based Sensors with Backtracking. Alexander Mendelsohn, Donald Sofge, Michael W. Otte |
| 2024 | Entropy Seeking Constrained Multiagent Reinforcement Learning. Ayhan Alp Aydeniz, Enrico Marchesini, Christopher Amato, Kagan Tumer |
| 2024 | Episodic Reinforcement Learning with Expanded State-reward Space. Dayang Liang, Yaru Zhang, Yunlong Liu |
| 2024 | Ethical Markov Decision Processes with Moral Worth as Rewards. Mihail Stojanovski, Nadjet Bourdache, Grégory Bonnet, Abdel-Illah Mouaddib |
| 2024 | Evaluating District-based Election Surveys with Synthetic Dirichlet Likelihood. Adway Mitra, Palash Dey |
| 2024 | Evaluation of Robustness of Off-Road Autonomous Driving Segmentation against Adversarial Attacks: A Dataset-Centric Study. Pankaj Deoli, Rohit Kumar, Axel Vierling, Karsten Berns |
| 2024 | Explainable Agents (XAg) by Design. Sebastian Rodriguez, John Thangarajah |
| 2024 | Explaining Sequences of Actions in Multi-agent Deep Reinforcement Learning Models. Khaing Phyo Wai, Minghong Geng, Shubham Pateria, Budhitama Subagdja, Ah-Hwee Tan |
| 2024 | Explaining the Behavior of POMDP-based Agents Through the Impact of Counterfactual Information. Saaduddin Mahmud, Marcell Vazquez-Chanlatte, Stefan J. Witwicki, Shlomo Zilberstein |
| 2024 | Extended Abstract of Diffusion Auction Design with Transaction Costs. Bin Li, Dong Hao, Dengji Zhao |
| 2024 | Extended Abstract: Price of Anarchy of Traffic Assignment with Exponential Cost Functions. Jianglin Qiao, Dave de Jonge, Dongmo Zhang, Simeon Simoff, Carles Sierra, Bo Du |
| 2024 | Extended Ranking Mechanisms for the m-Capacitated Facility Location Problem in Bayesian Mechanism Design. Gennaro Auricchio, Jie Zhang, Mengxiao Zhang |
| 2024 | Facility Location Games with Fractional Preferences and Limited Resources. Jiazhu Fang, Wenjing Liu |
| 2024 | Facility Location Games with Scaling Effects. Yu He, Alexander Lam, Minming Li |
| 2024 | Facility Location Games with Task Allocation. Zifan Gong, Minming Li, Houyu Zhou |
| 2024 | Factor Graph Neural Network Meets Max-Sum: A Real-Time Route Planning Algorithm for Massive-Scale Trips. Yixuan Li, Wanyuan Wang, Weiyi Xu, Yanchen Deng, Weiwei Wu |
| 2024 | Factored MDP based Moving Target Defense with Dynamic Threat Modeling. Megha Bose, Praveen Paruchuri, Akshat Kumar |
| 2024 | Fair Allocation of Conflicting Courses under Additive Utilities. Arpita Biswas, Yiduo Ke, Samir Khuller, Quanquan C. Liu |
| 2024 | Fair Scheduling of Indivisible Chores. Yatharth Kumar, Sarfaraz Equbal, Rohit Gurjar, Swaprava Nath, Rohit Vaish |
| 2024 | Fair and Efficient Division of a Discrete Cake with Switching Utility Loss. Zheng Chen, Bo Li, Minming Li, Guochuan Zhang |
| 2024 | Fairness and Cooperation between Independent Reinforcement Learners through Indirect Reciprocity. Jacobus Smit, Fernando P. Santos |
| 2024 | Fairness and Efficiency Trade-off in Two-sided Matching. Sung-Ho Cho, Kei Kimura, Kiki Liu, Kwei-guu Liu, Zhengjie Liu, Zhaohong Sun, Kentaro Yahiro, Makoto Yokoo |
| 2024 | Fairness and Privacy Guarantees in Federated Contextual Bandits. Sambhav Solanki, Sujit Gujar, Shweta Jain |
| 2024 | Fairness in Repeated House Allocation. Karl Jochen Micheel, Anaëlle Wilczynski |
| 2024 | Fairness of Exposure in Online Restless Multi-armed Bandits. Archit Sood, Shweta Jain, Sujit Gujar |
| 2024 | Fast and Slow Goal Recognition. Mattia Chiari, Alfonso Emilio Gerevini, Andrea Loreggia, Luca Putelli, Ivan Serina |
| 2024 | Finding Effective Ad Allocations: How to Exploit User History. Matteo Castiglioni, Alberto Latino, Alberto Marchesi, Giulia Romano, Nicola Gatti, Chokha Palayamkottai |
| 2024 | Fine-Grained Liquid Democracy for Cumulative Ballots. Matthias Köppe, Martin Koutecký, Krzysztof Sornat, Nimrod Talmon |
| 2024 | First 100 days of Pandemic: An Interplay of Pharmaceutical, Behavioral and Digital Interventions - A Study using Agent Based Modeling. Gauri Gupta, Ritvik Kapila, Ayush Chopra, Ramesh Raskar |
| 2024 | Forecasting and Mitigating Disruptions in Public Bus Transit Services. Chaeeun Han, Jose Paolo Talusan, Daniel Freudberg, Ayan Mukhopadhyay, Abhishek Dubey, Aron Laszka |
| 2024 | Foresight Distribution Adjustment for Off-policy Reinforcement Learning. Ruifeng Chen, Xu-Hui Liu, Tian-Shuo Liu, Shengyi Jiang, Feng Xu, Yang Yu |
| 2024 | Formal and Natural Language assisted Curriculum Generation for Reinforcement Learning Agents. Yash Shukla |
| 2024 | From Explicit Communication to Tacit Cooperation: A Novel Paradigm for Cooperative MARL. Dapeng Li, Zhiwei Xu, Bin Zhang, Guangchong Zhou, Zeren Zhang, Guoliang Fan |
| 2024 | From Market Saturation to Social Reinforcement: Understanding the Impact of Non-Linearity in Information Diffusion Models. Tobias Friedrich, Andreas Göbel, Nicolas Klodt, Martin S. Krejca, Marcus Pappik |
| 2024 | Frugal Actor-Critic: Sample Efficient Off-Policy Deep Reinforcement Learning Using Unique Experiences. Nikhil Kumar Singh, Indranil Saha |
| 2024 | Fully Independent Communication in Multi-Agent Reinforcement Learning. Rafael Pina, Varuna De Silva, Corentin Artaud, Xiaolan Liu |
| 2024 | Fuzzy Clustered Federated Learning Under Mixed Data Distributions. Peng Tang, Lifan Wang, Weidong Qiu, Zheng Huang, Qiangmin Wang |
| 2024 | GLIDE-RL: Grounded Language Instruction through DEmonstration in RL. Chaitanya Kharyal, Sai Krishna Gottipati, Tanmay Kumar Sinha, Srijita Das, Matthew E. Taylor |
| 2024 | GOV-REK: Governed Reward Engineering Kernels for Designing Robust Multi-Agent Reinforcement Learning Systems. Ashish Rana, Michael Oesterle, Jannik Brinkmann |
| 2024 | Game Transformations That Preserve Nash Equilibria or Best-Response Sets. Emanuel Tewolde, Vincent Conitzer |
| 2024 | Gaze Supervision for Mitigating Causal Confusion in Driving Agents. Abhijat Biswas, Badal Arun Pardhi, Caleb Chuck, Jarrett Holtz, Scott Niekum, Henny Admoni, Alessandro Allievi |
| 2024 | Generalized Response Objectives for Strategy Exploration in Empirical Game-Theoretic Analysis. Yongzhao Wang, Michael P. Wellman |
| 2024 | Generalized Strategy Synthesis of Infinite-state Impartial Combinatorial Games via Exact Binary Classification. Liangda Fang, Meihong Yang, Dingliang Cheng, Yunlai Hao, Quanlong Guan, Liping Xiong |
| 2024 | Generalizing Objective-Specification in Markov Decision Processes. Pedro P. Santos |
| 2024 | Generating and Choosing Organizations for Multi-Agent Systems. Cleber Jorge Amaral, Jomi F. Hübner, Stephen Cranefield |
| 2024 | Geospatial Active Search for Preventing Evictions. Anindya Sarkar, Alex DiChristofano, Sanmay Das, Patrick J. Fowler, Nathan Jacobs, Yevgeniy Vorobeychik |
| 2024 | Gerrymandering Planar Graphs. Jack Dippel, Max Dupré la Tour, April Niu, Sanjukta Roy, Adrian Vetta |
| 2024 | Going Beyond Mono-Mission Earth Observation: Using the Multi-Agent Paradigm to Federate Multiple Missions. Jean-Loup Farges, Filipo Perotto, Gauthier Picard, Cédric Pralet, Cyrille de Lussy, Jonathan Guerra, Philippe Pavero, Fabrice Planchou |
| 2024 | GraphSAID: Graph Sampling via Attention based Integer Programming Method. Ziqi Liu, Laurence Liu |
| 2024 | Grasper: A Generalist Pursuer for Pursuit-Evasion Problems. Pengdeng Li, Shuxin Li, Xinrun Wang, Jakub Cerný, Youzhi Zhang, Stephen McAleer, Hau Chan, Bo An |
| 2024 | Guided Exploration in Reinforcement Learning via Monte Carlo Critic Optimization. Igor Kuznetsov |
| 2024 | HELP! Providing Proactive Support in the Presence of Knowledge Asymmetry. Turgay Caglar, Sarath Sreedharan |
| 2024 | HLG: Bridging Human Heuristic Knowledge and Deep Reinforcement Learning for Optimal Agent Performance. Bin Chen, Zehong Cao |
| 2024 | HiMAP: Learning Heuristics-Informed Policies for Large-Scale Multi-Agent Pathfinding. Huijie Tang, Federico Berto, Zihan Ma, Chuanbo Hua, Kyuree Ahn, Jinkyoo Park |
| 2024 | High-Level, Collaborative Task Planning Grammar and Execution for Heterogeneous Agents. Amy Fang, Hadas Kress-Gazit |
| 2024 | Higher Order Reasoning under Intent Uncertainty Reinforces the Hobbesian Trap. Otto Kuusela, Debraj Roy |
| 2024 | Holonic Learning: A Flexible Agent-based Distributed Machine Learning Framework. Ahmad Esmaeili, Zahra Ghorrati, Eric T. Matson |
| 2024 | Human Goal Recognition as Bayesian Inference: Investigating the Impact of Actions, Timing, and Goal Solvability. Chenyuan Zhang, Charles Kemp, Nir Lipovetzky |
| 2024 | Hybrid Participatory Budgeting: Divisible, Indivisible, and Beyond. Gogulapati Sreedurga |
| 2024 | Hyper Strategy Logic. Raven Beutner, Bernd Finkbeiner |
| 2024 | IDIL: Imitation Learning of Intent-Driven Expert Behavior. Sangwon Seo, Vaibhav V. Unhelkar |
| 2024 | Imitation Learning Datasets: A Toolkit For Creating Datasets, Training Agents and Benchmarking. Nathan Gavenski, Michael Luck, Odinaldo Rodrigues |
| 2024 | Impact of Tie-Breaking on the Manipulability of Elections. James P. Bailey, Craig A. Tovey |
| 2024 | Improving Mobile Maternal and Child Health Care Programs: Collaborative Bandits for Time Slot Selection. Soumyabrata Pal, Milind Tambe, Arun Suggala, Karthikeyan Shanmugam, Aparna Taneja |
| 2024 | Incentive-based MARL Approach for Commons Dilemmas in Property-based Environments. Lukasz Pelcner, Matheus Aparecido do Carmo Alves, Leandro Soriano Marcolino, Paula A. Harrison, Peter M. Atkinson |
| 2024 | Incentives for Early Arrival in Cooperative Games. Yaoxin Ge, Yao Zhang, Dengji Zhao, Zhihao Gavin Tang, Hu Fu, Pinyan Lu |
| 2024 | Indirect Credit Assignment in a Multiagent System. Everardo Gonzalez, Siddarth Viswanathan, Kagan Tumer |
| 2024 | Inferring Lewisian Common Knowledge using Theory of Mind Reasoning in a Forward-chaining Rule Engine. Stephen Cranefield, Sriashalya Srivathsan, Jeremy Pitt |
| 2024 | Influence-Focused Asymmetric Island Model. Andrew Festa, Gaurav Dixit, Kagan Tumer |
| 2024 | Informativeness of Reward Functions in Reinforcement Learning. Rati Devidze, Parameswaran Kamalaruban, Adish Singla |
| 2024 | Interactive Control and Decision-Making for Multi-Robots Systems. Yiwei Lyu |
| 2024 | Interactively Learning the User's Utility for Best-Arm Identification in Multi-Objective Multi-Armed Bandits. Mathieu Reymond, Eugenio Bargiacchi, Diederik M. Roijers, Ann Nowé |
| 2024 | Is Limited Information Enough? An Approximate Multi-agent Coverage Control in Non-Convex Discrete Environments. Tatsuya Iwase, Aurélie Beynier, Nicolas Bredèche, Nicolas Maudet, Jason R. Marden |
| 2024 | It Is Among Us: Identifying Adversaries in Ad-hoc Domains using Q-valued Bayesian Estimations. Matheus Aparecido do Carmo Alves, Amokh Varma, Yehia Elkhatib, Leandro Soriano Marcolino |
| 2024 | JDRec: Practical Actor-Critic Framework for Online Combinatorial Recommender System. Xin Zhao, Jiaxin Li, Zhiwei Fang, Yuchen Guo, Jinyuan Zhao, Jie He, Wenlong Chen, Changping Peng, Guiguang Ding |
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| 2024 | Joint Intrinsic Motivation for Coordinated Exploration in Multi-Agent Deep Reinforcement Learning. Maxime Toquebiau, Nicolas Bredèche, Faïz Ben Amar, Jae-Yun Jun |
| 2024 | Keeping the Harmony Between Neighbors: Local Fairness in Graph Fair Division. Halvard Hummel, Ayumi Igarashi |
| 2024 | LLM-Powered Hierarchical Language Agent for Real-time Human-AI Coordination. Jijia Liu, Chao Yu, Jiaxuan Gao, Yuqing Xie, Qingmin Liao, Yi Wu, Yu Wang |
| 2024 | Large Language Model Assissted Multi-Agent Dialogue for Ontology Alignment. Shiyao Zhang, Yuji Dong, Yichuan Zhang, Terry R. Payne, Jie Zhang |
| 2024 | Large Learning Agents: Towards Continually Aligned Robots with Scale in RL. Bram Grooten |
| 2024 | Learning Complex Teamwork Tasks using a Given Sub-task Decomposition. Elliot Fosong, Arrasy Rahman, Ignacio Carlucho, Stefano V. Albrecht |
| 2024 | Learning Partner Selection Rules that Sustain Cooperation in Social Dilemmas with the Option of Opting Out. Chin-wing Leung, Paolo Turrini |
| 2024 | Learning a Social Network by Influencing Opinions. Dmitry Chistikov, Luisa Estrada, Mike Paterson, Paolo Turrini |
| 2024 | Learning and Calibrating Heterogeneous Bounded Rational Market Behaviour with Multi-agent Reinforcement Learning. Benjamin Patrick Evans, Sumitra Ganesh |
| 2024 | Learning and Sustaining Shared Normative Systems via Bayesian Rule Induction in Markov Games. Ninell Oldenburg, Tan Zhi-Xuan |
| 2024 | Learning to Schedule Online Tasks with Bandit Feedback. Yongxin Xu, Shangshang Wang, Hengquan Guo, Xin Liu, Ziyu Shao |
| 2024 | Leveraging Approximate Model-based Shielding for Probabilistic Safety Guarantees in Continuous Environments. Alexander W. Goodall, Francesco Belardinelli |
| 2024 | Leveraging Interpretable Human Models to Personalize AI Interventions for Behavior Change. Eura Nofshin |
| 2024 | Leveraging Sub-Optimal Data for Human-in-the-Loop Reinforcement Learning. Calarina Muslimani, Matthew E. Taylor |
| 2024 | LgTS: Dynamic Task Sampling using LLM-generated Sub-Goals for Reinforcement Learning Agents. Yash Shukla, Wenchang Gao, Vasanth Sarathy, Alvaro Velasquez, Robert Wright, Jivko Sinapov |
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| 2024 | Liquid Democracy for Low-Cost Ensemble Pruning. Ben Armstrong, Kate Larson |
| 2024 | MA-MIX: Value Function Decomposition for Cooperative Multiagent Reinforcement Learning Based on Multi-Head Attention Mechanism. Yu Niu, Hengxu Zhao, Lei Yu |
| 2024 | MABL: Bi-Level Latent-Variable World Model for Sample-Efficient Multi-Agent Reinforcement Learning. Aravind Venugopal, Stephanie Milani, Fei Fang, Balaraman Ravindran |
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| 2024 | MATLight: Traffic Signal Coordinated Control Algorithm based on Heterogeneous-Agent Mirror Learning with Transformer. Haipeng Zhang, Zhiwen Wang, Na Li |
| 2024 | MESA: Cooperative Meta-Exploration in Multi-Agent Learning through Exploiting State-Action Space Structure. Zhicheng Zhang, Yancheng Liang, Yi Wu, Fei Fang |
| 2024 | MaDi: Learning to Mask Distractions for Generalization in Visual Deep Reinforcement Learning. Bram Grooten, Tristan Tomilin, Gautham Vasan, Matthew E. Taylor, A. Rupam Mahmood, Meng Fang, Mykola Pechenizkiy, Decebal Constantin Mocanu |
| 2024 | Majority-based Preference Diffusion on Social Networks. Ahad N. Zehmakan |
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| 2024 | Mechanism Design for Reducing Agent Distances to Prelocated Facilities. Hau Chan, Xinliang Fu, Minming Li, Chenhao Wang |
| 2024 | Memory-Based Resilient Control Against Non-cooperation in Multi-agent Flocking. Mingyue Zhang, Nianyu Li, Jialong Li, Jiachun Liao, Jiamou Liu |
| 2024 | Metric Distortion Under Public-Spirited Voting. Amirreza Bagheridelouee, Marzie Nilipour, Masoud Seddighin, Maziar Shamsipour |
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| 2024 | Minimax Exploiter: A Data Efficient Approach for Competitive Self-Play. Daniel Bairamian, Philippe Marcotte, Joshua Romoff, Gabriel Robert, Derek Nowrouzezahrai |
| 2024 | Minimizing Negative Side Effects in Cooperative Multi-Agent Systems using Distributed Coordination. Moumita Choudhury, Sandhya Saisubramanian, Hao Zhang, Shlomo Zilberstein |
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| 2024 | Mixed-Initiative Bayesian Sub-Goal Optimization in Hierarchical Reinforcement Learning. Haozhe Ma, Thanh Vinh Vo, Tze-Yun Leong |
| 2024 | Mixed-Initiative Human-Robot Teaming under Suboptimality with Online Bayesian Adaptation. Manisha Natarajan, Chunyue Xue, Sanne van Waveren, Karen M. Feigh, Matthew C. Gombolay |
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| 2024 | Modelling the Dynamics of Subjective Identity in Allocation Games. Janvi Chhabra, Jayati Deshmukh, Srinath Srinivasa |
| 2024 | Modelling the Rise and Fall of Two-sided Markets. Farnoud Ghasemi, Rafal Kucharski |
| 2024 | Monitored Markov Decision Processes. Simone Parisi, Montaser Mohammedalamen, Alireza Kazemipour, Matthew E. Taylor, Michael Bowling |
| 2024 | Monitoring Second-Order Hyperproperties. Raven Beutner, Bernd Finkbeiner, Hadar Frenkel, Niklas Metzger |
| 2024 | Multi-Agent Alternate Q-Learning. Kefan Su, Siyuan Zhou, Jiechuan Jiang, Chuang Gan, Xiangjun Wang, Zongqing Lu |
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| 2024 | Multi-Agent Reinforcement Learning for Assessing False-Data Injection Attacks on Transportation Networks. Taha Eghtesad, Sirui Li, Yevgeniy Vorobeychik, Aron Laszka |
| 2024 | Multi-Robot Allocation of Assistance from a Shared Uncertain Operator. Clarissa Costen, Anna Gautier, Nick Hawes, Bruno Lacerda |
| 2024 | Multi-Robot Motion and Task Planning in Automotive Production Using Controller-based Safe Reinforcement Learning. Eric Wete, Joel Greenyer, Daniel Kudenko, Wolfgang Nejdl |
| 2024 | Multi-deal Negotiation. Tim Baarslag |
| 2024 | Multi-level Aggregation with Delays and Stochastic Arrivals. Mathieu Mari, Michal Pawlowski, Runtian Ren, Piotr Sankowski |
| 2024 | Multi-user Norm Consensus. Marc Serramia, Natalia Criado, Michael Luck |
| 2024 | Multimodal Pretrained Models for Verifiable Sequential Decision-Making: Planning, Grounding, and Perception. Yunhao Yang, Cyrus Neary, Ufuk Topcu |
| 2024 | Mutual Information as Intrinsic Reward of Reinforcement Learning Agents for On-demand Ride Pooling. Xianjie Zhang, Jiahao Sun, Chen Gong, Kai Wang, Yifei Cao, Hao Chen, Yu Liu |
| 2024 | NP Joanna Kaczmarek, Jörg Rothe |
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| 2024 | Nash Stability in Hedonic Skill Games. Laurent Gourvès, Gianpiero Monaco |
| 2024 | Near-Optimal Online Resource Allocation in the Random-Order Model. Saar Cohen, Noa Agmon |
| 2024 | Negotiation Strategies for Combining Partials Deals in One-To-Many Negotiations. Tamara C. P. Florijn |
| 2024 | Network Agency: An Agent-based Model of Forced Migration from Ukraine. Zakaria Mehrab, Logan Stundal, Samarth Swarup, Srinivasan Venkatramanan, Bryan Lewis, Henning S. Mortveit, Christopher L. Barrett, Abhishek Pandey, Chad R. Wells, Alison P. Galvani, Burton H. Singer, David Leblang, Rita R. Colwell, Madhav V. Marathe |
| 2024 | Neural Population Learning beyond Symmetric Zero-Sum Games. Siqi Liu, Luke Marris, Marc Lanctot, Georgios Piliouras, Joel Z. Leibo, Nicolas Heess |
| 2024 | Neurological Based Timing Mechanism for Reinforcement Learning. Michael J. Tarlton, Gustavo B. M. Mello, Anis Yazidi |
| 2024 | New Algorithms for Distributed Fair k-Center Clustering: Almost Accurate as Sequential Algorithms. Xiaoliang Wu, Qilong Feng, Ziyun Huang, Jinhui Xu, Jianxin Wang |
| 2024 | No Transaction Fees? No Problem! Achieving Fairness in Transaction Fee Mechanism Design. Sankarshan Damle, Varul Srivastava, Sujit Gujar |
| 2024 | Non Stationary Bandits with Periodic Variation. Titas Chakraborty, Parth Shettiwar |
| 2024 | Norm Enforcement with a Soft Touch: Faster Emergence, Happier Agents. Sz-Ting Tzeng, Nirav Ajmeri, Munindar P. Singh |
| 2024 | Normalization Enhances Generalization in Visual Reinforcement Learning. Lu Li, Jiafei Lyu, Guozheng Ma, Zilin Wang, Zhenjie Yang, Xiu Li, Zhiheng Li |
| 2024 | NovelGym: A Flexible Ecosystem for Hybrid Planning and Learning Agents Designed for Open Worlds. Shivam Goel, Yichen Wei, Panagiotis Lymperopoulos, Klára Churá, Matthias Scheutz, Jivko Sinapov |
| 2024 | ODEs Learn to Walk: ODE-Net based Data-Driven Modeling for Crowd Dynamics. Chen Cheng, Jinglai Li |
| 2024 | OPEx: A Large Language Model-Powered Framework for Embodied Instruction Following. Haochen Shi, Zhiyuan Sun, Xingdi Yuan, Marc-Alexandre Côté, Bang Liu |
| 2024 | Observer-Aware Planning with Implicit and Explicit Communication. Shuwa Miura, Shlomo Zilberstein |
| 2024 | Obstruction Alternating-time Temporal Logic: A Strategic Logic to Reason about Dynamic Models. Davide Catta, Jean Leneutre, Vadim Malvone, Aniello Murano |
| 2024 | Offline Risk-sensitive RL with Partial Observability to Enhance Performance in Human-Robot Teaming. Giorgio Angelotti, Caroline P. C. Chanel, Adam Henrique Moreira Pinto, Christophe Lounis, Corentin Chauffaut, Nicolas Drougard |
| 2024 | Oh, Now I See What You Want: Learning Agent Models with Internal States from Observations. Panagiotis Lymperopoulos, Matthias Scheutz |
| 2024 | On Dealing with False Beliefs and Maintaining KD45 Tran Cao Son, Loc Pham, Enrico Pontelli |
| 2024 | On General Epistemic Abstract Argumentation Frameworks. Gianvincenzo Alfano, Sergio Greco, Francesco Parisi, Irina Trubitsyna |
| 2024 | On Green Sustainability of Resource Selection Games with Equitable Cost-Sharing. Vittorio Bilò, Michele Flammini, Gianpiero Monaco, Luca Moscardelli, Cosimo Vinci |
| 2024 | On the Complexity of Candidates-Embedded Multiwinner Voting under the Hausdorff Function. Yongjie Yang |
| 2024 | On the Complexity of Pareto-Optimal and Envy-Free Lotteries. Ioannis Caragiannis, Kristoffer Arnsfelt Hansen, Nidhi Rathi |
| 2024 | On the Computational Complexity of Quasi-Variational Inequalities and Multi-Leader-Follower Games. Bruce M. Kapron, Koosha Samieefar |
| 2024 | On the Potential and Limitations of Proxy Voting: Delegation with Incomplete Votes. Georgios Amanatidis, Aris Filos-Ratsikas, Philip Lazos, Evangelos Markakis, Georgios Papasotiropoulos |
| 2024 | On the Stability of Learning in Network Games with Many Players. Aamal Abbas Hussain, Dan Leonte, Francesco Belardinelli, Georgios Piliouras |
| 2024 | On the Transit Obfuscation Problem. Hideaki Takahashi, Alex Fukunaga |
| 2024 | On the Utility of External Agent Intention Predictor for Human-AI Coordination. Chenxu Wang, Zilong Chen, Huaping Liu |
| 2024 | On the existence of EFX under picky or non-differentiative agents. Maya Viswanathan, Ruta Mehta |
| 2024 | Online Decentralised Mechanisms for Dynamic Ridesharing. Nicos Protopapas, Vahid Yazdanpanah, Enrico H. Gerding, Sebastian Stein |
| 2024 | Ontological Modeling and Reasoning for Comparison and Contrastive Narration of Robot Plans. Alberto Olivares Alarcos, Sergi Foix, Júlia Borràs Sol, Gerard Canal, Guillem Alenyà |
| 2024 | Opinion Diffusion on Society Graphs Based on Approval Ballots. Jayakrishnan Madathil, Neeldhara Misra, Yash More |
| 2024 | Optimal Diffusion Auctions. Yao Zhang, Shanshan Zheng, Dengji Zhao |
| 2024 | Optimal Flash Loan Fee Function with Respect to Leverage Strategies. Chenmin Wang, Peng Li, Yulong Zeng, Xuepeng Fan |
| 2024 | Optimal Majority Rules and Quantitative Condorcet Properties of Setwise Kemeny Voting Schemes. Xuan Kien Phung, Sylvie Hamel |
| 2024 | Optimal Referral Auction Design. Rangeet Bhattacharyya, Parvik Dave, Palash Dey, Swaprava Nath |
| 2024 | Optimal Task Assignment and Path Planning using Conflict-Based Search with Precedence and Temporal Constraints. Yu Quan Chong, Jiaoyang Li, Katia P. Sycara |
| 2024 | Overview of t-DGR: A Trajectory-Based Deep Generative Replay Method for Continual Learning in Decision Making. William Yue, Bo Liu, Peter Stone |
| 2024 | PADDLE: Logic Program Guided Policy Reuse in Deep Reinforcement Learning. Hao Zhang, Tianpei Yang, Yan Zheng, Jianye Hao, Matthew E. Taylor |
| 2024 | PAS: Probably Approximate Safety Verification of Reinforcement Learning Policy Using Scenario Optimization. Arambam James Singh, Arvind Easwaran |
| 2024 | PDiT: Interleaving Perception and Decision-making Transformers for Deep Reinforcement Learning. Hangyu Mao, Rui Zhao, Ziyue Li, Zhiwei Xu, Hao Chen, Yiqun Chen, Bin Zhang, Zhen Xiao, Junge Zhang, Jiangjin Yin |
| 2024 | PI-NeuGODE: Physics-Informed Graph Neural Ordinary Differential Equations for Spatiotemporal Trajectory Prediction. Zhaobin Mo, Yongjie Fu, Xuan Di |
| 2024 | Parameterized Guarantees for Almost Envy-Free Allocations. Siddharth Barman, Debajyoti Kar, Shraddha Pathak |
| 2024 | Persuasion by Shaping Beliefs about Multidimensional Features of a Thing. Kazunori Terada, Yasuo Noma, Masanori Hattori |
| 2024 | Playing Quantitative Games Against an Authority: On the Module Checking Problem. Wojciech Jamroga, Munyque Mittelmann, Aniello Murano, Giuseppe Perelli |
| 2024 | Policy Learning for Off-Dynamics RL with Deficient Support. Linh Le Pham Van, Hung The Tran, Sunil Gupta |
| 2024 | Policy Optimization using Horizon Regularized Advantage to Improve Generalization in Reinforcement Learning. Nasik Muhammad Nafi, Raja Farrukh Ali, William H. Hsu, Kevin Duong, Mason Vick |
| 2024 | Policy-regularized Offline Multi-objective Reinforcement Learning. Qian Lin, Chao Yu, Zongkai Liu, Zifan Wu |
| 2024 | Population Synthesis as Scenario Generation for Simulation-based Planning under Uncertainty. Joel Dyer, Arnau Quera-Bofarull, Nicholas Bishop, J. Doyne Farmer, Anisoara Calinescu, Michael J. Wooldridge |
| 2024 | Population-aware Online Mirror Descent for Mean-Field Games by Deep Reinforcement Learning. Zida Wu, Mathieu Laurière, Samuel Jia Cong Chua, Matthieu Geist, Olivier Pietquin, Ankur Mehta |
| 2024 | Positive Intra-Group Externalities in Facility Location. Ying Wang, Houyu Zhou, Minming Li |
| 2024 | Potential Games on Cubic Splines for Multi-Agent Motion Planning of Autonomous Agents. Sam Williams, Jyotirmoy Deshmukh |
| 2024 | Potential-Based Reward Shaping for Intrinsic Motivation. Grant C. Forbes, Nitish Gupta, Leonardo Villalobos-Arias, Colin M. Potts, Arnav Jhala, David L. Roberts |
| 2024 | Pragmatic Instruction Following and Goal Assistance via Cooperative Language-Guided Inverse Planning. Tan Zhi-Xuan, Lance Ying, Vikash Mansinghka, Joshua B. Tenenbaum |
| 2024 | Predicting and Protecting the Cognitive Health of Operators in Isolated, Confined, and Extreme Environments. Erin E. Richardson |
| 2024 | Preventing Deadlocks for Multi-Agent Pickup and Delivery in Dynamic Environments. Benedetta Flammini, Davide Azzalini, Francesco Amigoni |
| 2024 | Private Agent-Based Modeling. Ayush Chopra, Arnau Quera-Bofarull, Nurullah Giray Kuru, Michael J. Wooldridge, Ramesh Raskar |
| 2024 | Probabilistic Multi-agent Only-Believing. Qihui Feng, Gerhard Lakemeyer |
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| 2024 | Projection-Optimal Monotonic Value Function Factorization in Multi-Agent Reinforcement Learning. Yongsheng Mei, Hanhan Zhou, Tian Lan |
| 2024 | Proportional Fairness in Obnoxious Facility Location. Alexander Lam, Haris Aziz, Bo Li, Fahimeh Ramezani, Toby Walsh |
| 2024 | Provably Learning Nash Policies in Constrained Markov Potential Games. Pragnya Alatur, Giorgia Ramponi, Niao He, Andreas Krause |
| 2024 | Pruning Neural Networks Using Cooperative Game Theory. Mauricio Diaz-Ortiz Jr., Benjamin Kempinski, Daphne Cornelisse, Yoram Bachrach, Tal Kachman |
| 2024 | Psychophysiological Models of Cognitive States Can Be Operator-Agnostic. Erin E. Richardson, Savannah Lynn Buchner, Jacob R. Kintz, Torin K. Clark, Allison P. Anderson |
| 2024 | Pure Nash Equilibria in Weighted Congestion Games with Complementarities and Beyond. Kenjiro Takazawa |
| 2024 | Quantifying Agent Interaction in Multi-agent Reinforcement Learning for Cost-efficient Generalization. Yuxin Chen, Chen Tang, Ran Tian, Chenran Li, Jinning Li, Masayoshi Tomizuka, Wei Zhan |
| 2024 | Quantum Circuit Design: A Reinforcement Learning Challenge. Philipp Altmann, Adelina Bärligea, Jonas Stein, Michael Kölle, Thomas Gabor, Thomy Phan, Claudia Linnhoff-Popien |
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| 2024 | RAISE the Bar: Restriction of Action Spaces for Improved Social Welfare and Equity in Traffic Management. Michael Oesterle, Tim Grams, Christian Bartelt, Heiner Stuckenschmidt |
| 2024 | Rational Verification with Quantitative Probabilistic Goals. David Hyland, Julian Gutierrez, Shankaranarayanan Krishna, Michael J. Wooldridge |
| 2024 | Recourse under Model Multiplicity via Argumentative Ensembling. Junqi Jiang, Francesco Leofante, Antonio Rago, Francesca Toni |
| 2024 | Reducing Optimism Bias in Incomplete Cooperative Games. Filip Úradník, David Sychrovský, Jakub Cerný, Martin Cerný |
| 2024 | Reducing Systemic Risk in Financial Networks through Donations. Jinyun Tong, Bart de Keijzer, Carmine Ventre |
| 2024 | Regret-based Defense in Adversarial Reinforcement Learning. Roman Belaire, Pradeep Varakantham, Thanh Hong Nguyen, David Lo |
| 2024 | Reinforcement Learning Interventions on Boundedly Rational Human Agents in Frictionful Tasks. Eura Nofshin, Siddharth Swaroop, Weiwei Pan, Susan A. Murphy, Finale Doshi-Velez |
| 2024 | Reinforcement Learning for Question Answering in Programming Domain using Public Community Scoring as a Human Feedback. Alexey Gorbatovski, Sergey V. Kovalchuk |
| 2024 | Reinforcement Learning in the Wild with Maximum Likelihood-based Model Transfer. Hannes Eriksson, Tommy Tram, Debabrota Basu, Mina Alibeigi, Christos Dimitrakakis |
| 2024 | Reinforcement Learning with Ensemble Model Predictive Safety Certification. Sven Gronauer, Tom Haider, Felippe Schmoeller da Roza, Klaus Diepold |
| 2024 | Reinforcement Nash Equilibrium Solver. Xinrun Wang, Chang Yang, Shuxin Li, Pengdeng Li, Xiao Huang, Hau Chan, Bo An |
| 2024 | Relaxed Exploration Constrained Reinforcement Learning. Shahaf S. Shperberg, Bo Liu, Peter Stone |
| 2024 | Rethinking Out-of-Distribution Detection for Reinforcement Learning: Advancing Methods for Evaluation and Detection. Linas Nasvytis, Kai Sandbrink, Jakob N. Foerster, Tim Franzmeyer, Christian Schröder de Witt |
| 2024 | Risk-Aware Constrained Reinforcement Learning with Non-Stationary Policies. Zhaoxing Yang, Haiming Jin, Yao Tang, Guiyun Fan |
| 2024 | Risk-Sensitive Multi-Agent Reinforcement Learning in Network Aggregative Markov Games. Hafez Ghaemi, Hamed Kebriaei, Alireza Ramezani Moghaddam, Majid Nili Ahmadabadi |
| 2024 | Robust Knowledge Extraction from Large Language Models using Social Choice Theory. Nico Potyka, Yuqicheng Zhu, Yunjie He, Evgeny Kharlamov, Steffen Staab |
| 2024 | Robust Popular Matchings. Martin Bullinger, Rohith Reddy Gangam, Parnian Shahkar |
| 2024 | SMT4SMTL: A Tool for SMT-Based Satisfiability Checking of SMTL. Artur Niewiadomski, Maciej Nazarczuk, Mateusz Przychodzki, Magdalena Kacprzak, Wojciech Penczek, Andrzej Zbrzezny |
| 2024 | STV+KH: Towards Practical Verification of Strategic Ability for Knowledge and Information Flow. Mateusz Kaminski, Damian Kurpiewski, Wojciech Jamroga |
| 2024 | Safe Model-Based Multi-Agent Mean-Field Reinforcement Learning. Matej Jusup, Barna Pásztor, Tadeusz Janik, Kenan Zhang, Francesco Corman, Andreas Krause, Ilija Bogunovic |
| 2024 | Safe Reinforcement Learning with Free-form Natural Language Constraints and Pre-Trained Language Models. Xingzhou Lou, Junge Zhang, Ziyan Wang, Kaiqi Huang, Yali Du |
| 2024 | Safeguard Privacy for Minimal Data Collection with Trustworthy Autonomous Agents. Mengwei Xu, Louise A. Dennis, Mustafa A. Mustafa |
| 2024 | Sample and Communication Efficient Fully Decentralized MARL Policy Evaluation via a New Approach: Local TD Update. Hairi, Zifan Zhang, Jia Liu |
| 2024 | Scaling Opponent Shaping to High Dimensional Games. Akbir Khan, Timon Willi, Newton Kwan, Andrea Tacchetti, Chris Lu, Edward Grefenstette, Tim Rocktäschel, Jakob N. Foerster |
| 2024 | Scaling up Cooperative Multi-agent Reinforcement Learning Systems. Minghong Geng |
| 2024 | Selecting Representative Bodies: An Axiomatic View. Manon Revel, Niclas Boehmer, Rachael Colley, Markus Brill, Piotr Faliszewski, Edith Elkind |
| 2024 | Sentimental Agents: Combining Sentiment Analysis and Non-Bayesian Updating for Cooperative Decision-Making. Daniele Orner, Elizabeth Akinyi Ondula, Nick Mumero Mwangi, Richa Goyal |
| 2024 | Shield Decentralization for Safe Reinforcement Learning in General Partially Observable Multi-Agent Environments. Daniel Melcer, Christopher Amato, Stavros Tripakis |
| 2024 | Simple k-crashing Plan with a Good Approximation Ratio. Ruixi Luo, Kai Jin, Zelin Ye |
| 2024 | Simulated Robotic Soft Body Manipulation. Glareh Mir, Michael Beetz |
| 2024 | Simultaneously Achieving Group Exposure Fairness and Within-Group Meritocracy in Stochastic Bandits. Subham Pokhriyal, Shweta Jain, Ganesh Ghalme, Swapnil Dhamal, Sujit Gujar |
| 2024 | Single-Winner Voting with Alliances: Avoiding the Spoiler Effect. Grzegorz Pierczynski, Stanislaw Szufa |
| 2024 | Social Identities and Responsible Agency. Karthik Sama, Jayati Deshmukh, Srinath Srinivasa |
| 2024 | Solution-oriented Agent-based Models Generation with Verifier-assisted Iterative In-context Learning. Tong Niu, Weihao Zhang, Rong Zhao |
| 2024 | Solving Offline 3D Bin Packing Problem with Large-sized Bin via Two-stage Deep Reinforcement Learning. Hao Yin, Fan Chen, Hongjie He |
| 2024 | Solving Two-player Games with QBF Solvers in General Game Playing. Yifan He, Abdallah Saffidine, Michael Thielscher |
| 2024 | Source Detection in Networks using the Stationary Distribution of a Markov Chain. Yael Sabato, Amos Azaria, Noam Hazon |
| 2024 | Stability of Weighted Majority Voting under Estimated Weights. Shaojie Bai, Dongxia Wang, Tim Muller, Peng Cheng, Jiming Chen |
| 2024 | Strategic Cost Selection in Participatory Budgeting. Piotr Faliszewski, Lukasz Janeczko, Andrzej Kaczmarczyk, Grzegorz Lisowski, Piotr Skowron, Stanislaw Szufa |
| 2024 | Strategic Reasoning under Capacity-constrained Agents. Gabriel Ballot, Vadim Malvone, Jean Leneutre, Youssef Laarouchi |
| 2024 | Strategic Routing and Scheduling for Evacuations. Kazi Ashik Islam, Da Qi Chen, Madhav V. Marathe, Henning S. Mortveit, Samarth Swarup, Anil Vullikanti |
| 2024 | Successively Pruned Q-Learning: Using Self Q-function to Reduce the Overestimation. Zhaolin Xue, Lihua Zhang, Zhiyan Dong |
| 2024 | Surge Routing: Event-informed Multiagent Reinforcement Learning for Autonomous Rideshare. Daniel Garces, Stephanie Gil |
| 2024 | Symbolic Computation of Sequential Equilibria. Moritz Graf, Thorsten Engesser, Bernhard Nebel |
| 2024 | Synthesizing Social Laws with ATL Conditions. Rustam Galimullin, Louwe B. Kuijer |
| 2024 | TIMAT: Temporal Information Multi-Agent Transformer. Qitong Kang, Fuyong Wang, Zhongxin Liu, Zengqiang Chen |
| 2024 | Taking Agent-Based Social Simulation to the Next Level Using Exascale Computing: Potential Use-Cases, Capacity Requirements and Threats. Matthew P. Hare, Doug Salt, Ric Colasanti, Richard Milton, Mike Batty, Alison J. Heppenstall, Gary Polhill |
| 2024 | TaxAI: A Dynamic Economic Simulator and Benchmark for Multi-agent Reinforcement Learning. Qirui Mi, Siyu Xia, Yan Song, Haifeng Zhang, Shenghao Zhu, Jun Wang |
| 2024 | Team Performance and User Satisfaction in Mixed Human-Agent Teams. Sami Abuhaimed, Sandip Sen |
| 2024 | The Cognitive Hourglass: Agent Abstractions in the Large Models Era. Alessandro Ricci, Stefano Mariani, Franco Zambonelli, Samuele Burattini, Cristiano Castelfranchi |
| 2024 | The Multi-agent System based on LLM for Online Discussions. Yihan Dong |
| 2024 | The Parameterized Complexity of Welfare Guarantees in Schelling Segregation. Argyrios Deligkas, Eduard Eiben, Tiger-Lily Goldsmith |
| 2024 | The Reasons that Agents Act: Intention and Instrumental Goals. Francis Rhys Ward, Matt MacDermott, Francesco Belardinelli, Francesca Toni, Tom Everitt |
| 2024 | The Selfishness Level of Social Dilemmas. Stefan Roesch, Stefanos Leonardos, Yali Du |
| 2024 | The Stochastic Evolutionary Dynamics of Softmax Policy Gradient in Games. Chin-wing Leung, Shuyue Hu, Ho-fung Leung |
| 2024 | The Triangles of Dishonesty: Modelling the Evolution of Lies, Bullshit, and Deception in Agent Societies. Stefan Sarkadi, Peter R. Lewis |
| 2024 | Think Global, Act Local - Agent-Based Inline Recovery for Airline Operations. Yashovardhan S. Chati, Ramasubramanian Suriyanarayanan, Arunchandar Vasan |
| 2024 | Tight Approximations for Graphical House Allocation. Hadi Hosseini, Andrew McGregor, Rik Sengupta, Rohit Vaish, Vignesh Viswanathan |
| 2024 | Time-Constrained Restless Multi-Armed Bandits with Applications to City Service Scheduling. Yi Mao, Andrew Perrault |
| 2024 | To Lead or to be Led: A Generalized Condorcet Jury Theorem under Dependence. Jonas Karge, Juliette-Michelle Burkhardt, Sebastian Rudolph, Dominik Rusovac |
| 2024 | Toward Explainable Agent Behaviour. Victor Gimenez-Abalos |
| 2024 | Toward Socially Friendly Autonomous Driving Using Multi-agent Deep Reinforcement Learning. Jhih-Ching Yeh, Von-Wun Soo |
| 2024 | Toward a Normative Approach for Resilient Multiagent Systems: A Summary. Geeta Mahala, Özgür Kafali, Hoa Khanh Dam, Aditya Ghose, Munindar P. Singh |
| 2024 | Toward a Quality Model for Hybrid Intelligence Teams. Davide Dell'Anna, Pradeep K. Murukannaiah, Bernd Dudzik, Davide Grossi, Catholijn M. Jonker, Catharine Oertel, Pinar Yolum |
| 2024 | Towards Efficient Auction Design with ROI Constraints. Xinyu Tang, Hongtao Lv, Yingjie Gao, Fan Wu, Lei Liu, Lizhen Cui |
| 2024 | Towards Generalizability of Multi-Agent Reinforcement Learning in Graphs with Recurrent Message Passing. Jannis Weil, Zhenghua Bao, Osama Abboud, Tobias Meuser |
| 2024 | Towards Socially-Acceptable Multi-Criteria Resolution of the 4D-Contracts Repair Problem. Youssef Hamadi, Gauthier Picard |
| 2024 | Towards Sustainable Human-Agent Teams: A Framework for Understanding Human-Agent Team Dynamics. Rui Prada, Astrid C. Homan, Gerben A. van Kleef |
| 2024 | Towards Understanding How to Reduce Generalization Gap in Visual Reinforcement Learning. Jiafei Lyu, Le Wan, Xiu Li, Zongqing Lu |
| 2024 | Towards Zero Shot Learning in Restless Multi-armed Bandits. Yunfan Zhao, Nikhil Behari, Edward Hughes, Edwin Zhang, Dheeraj Nagaraj, Karl Tuyls, Aparna Taneja, Milind Tambe |
| 2024 | Towards a Principle-based Framework for Repair Selection in Inconsistent Knowledge Bases. Saïd Jabbour, Yue Ma, Badran Raddaoui |
| 2024 | Towards building Autonomous AI Agents and Robots for Open World Environments. Shivam Goel |
| 2024 | Trust in Shapley: A Cooperative Quest for Global Trust in P2P Network. Arti Bandhana, Tomás Kroupa, Sebastián García |
| 2024 | Trustworthy Reinforcement Learning: Opportunities and Challenges. Ann Nowé |
| 2024 | Truthful and Stable One-sided Matching on Networks. Tianyi Yang, Yuxiang Zhai, Dengji Zhao, Xinwei Song, Miao Li |
| 2024 | Uncoupled Learning of Differential Stackelberg Equilibria with Commitments. Robert T. Loftin, Mustafa Mert Çelikok, Herke van Hoof, Samuel Kaski, Frans A. Oliehoek |
| 2024 | Understanding the Impact of Promotions on Consumer Behavior. Jarod Vanderlynden, Philippe Mathieu, Romain Warlop |
| 2024 | Unifying Regret and State-Action Space Coverage for Effective Unsupervised Environment Design. Jayden Teoh Jing Teoh, Wenjun Li, Pradeep Varakantham |
| 2024 | Unlocking the Potential of Machine Ethics with Explainability. Timo Speith |
| 2024 | Unraveling the Tapestry of Deception and Personality: A Deep Dive into Multi-Issue Human-Agent Negotiation Dynamics. Nusrath Jahan, Johnathan Mell |
| 2024 | User-centric Explanation Strategies for Interactive Recommenders. Berk Buzcu, Emre Kuru, Reyhan Aydogan |
| 2024 | Utility-Based Reinforcement Learning: Unifying Single-objective and Multi-objective Reinforcement Learning. Peter Vamplew, Cameron Foale, Conor F. Hayes, Patrick Mannion, Enda Howley, Richard Dazeley, Scott Johnson, Johan Källström, Gabriel de Oliveira Ramos, Roxana Radulescu, Willem Röpke, Diederik M. Roijers |
| 2024 | Value Alignment in Participatory Budgeting. Marc Serramia, Maite López-Sánchez, Juan A. Rodríguez-Aguilar, Stefano Moretti |
| 2024 | Value-based Resource Matching with Fairness Criteria: Application to Agricultural Water Trading. Abhijin Adiga, Yohai Trabelsi, Tanvir Ferdousi, Madhav V. Marathe, S. S. Ravi, Samarth Swarup, Anil Kumar S. Vullikanti, Mandy L. Wilson, Sarit Kraus, Reetwika Basu, Supriya Savalkar, Matthew Yourek, Michael Brady, Kirti Rajagopalan, Jonathan Yoder |
| 2024 | Verification of Stochastic Multi-Agent Systems with Forgetful Strategies. Francesco Belardinelli, Wojtek Jamroga, Munyque Mittelmann, Aniello Murano |
| 2024 | Verifying Proportionality in Temporal Voting. Edith Elkind, Svetlana Obraztsova, Nicholas Teh |
| 2024 | Veto Core Consistent Preference Aggregation. Aleksei Y. Kondratev, Egor Ianovski |
| 2024 | Viral Marketing in Social Networks with Competing Products. Ahad N. Zehmakan, Xiaotian Zhou, Zhongzhi Zhang |
| 2024 | Weighted Proportional Allocations of Indivisible Goods and Chores: Insights via Matchings. Vishwa Prakash HV, Prajakta Nimbhorkar |
| 2024 | When is Mean-Field Reinforcement Learning Tractable and Relevant? Batuhan Yardim, Artur Goldman, Niao He |
| 2024 | Which Games are Unaffected by Absolute Commitments? Daji Landis, Nikolaj I. Schwartzbach |
| 2024 | Who gets the Maximal Extractable Value? A Dynamic Sharing Blockchain Mechanism. Pedro Braga, Georgios Chionas, Piotr Krysta, Stefanos Leonardos, Georgios Piliouras, Carmine Ventre |
| 2024 | Whom to Trust? Elective Learning for Distributed Gaussian Process Regression. Zewen Yang, Xiaobing Dai, Akshat Dubey, Sandra Hirche, Georges Hattab |
| 2024 | Willy Wonka Mechanisms. Thomas Archbold, Bart de Keijzer, Carmine Ventre |
| 2024 | flame: A Framework for Learning in Agent-based ModEls. Ayush Chopra, Jayakumar Subramanian, Balaji Krishnamurthy, Ramesh Raskar |
| 2024 | pgeon applied to Overcooked-AI to explain agents' behaviour. Adrián Tormos, Victor Gimenez-Abalos, Javier Vázquez-Salceda, Sergio Álvarez-Napagao |
| 2024 | vMFER: von Mises-Fisher Experience Resampling Based on Uncertainty of Gradient Directions for Policy Improvement of Actor-Critic Algorithms. Yiwen Zhu, Jinyi Liu, Wenya Wei, Qianyi Fu, Yujing Hu, Zhou Fang, Bo An, Jianye Hao, Tangjie Lv, Changjie Fan |