AAAI 2024

2,864 papers

Emergent Communication for Numerical Concepts Generalization

Enshuai Zhou, Yifan Hao, Rui Zhang, Yuxuan Guo, Zidong Du

Intrinsic Action Tendency Consistency for Cooperative Multi-Agent Reinforcement Learning

Junkai Zhang, Yifan Zhang, Xi Sheryl Zhang, Yifan Zang, Jian Cheng

ProAgent: Building Proactive Cooperative Agents with Large Language Models

Ceyao Zhang, Kaijie Yang, Siyi Hu, Zihao Wang, Guanghe Li

Leveraging Partial Symmetry for Multi-Agent Reinforcement Learning

Xin Yu, Rongye Shi, Pu Feng, Yongkai Tian, Simin Li

Robust Communicative Multi-Agent Reinforcement Learning with Active Defense

Lebin Yu, Yunbo Qiu, Quanming Yao, Yuan Shen, Xudong Zhang

Large-Scale Multi-Robot Coverage Path Planning via Local Search

Jingtao Tang, Hang Ma

Bidirectional Temporal Plan Graph: Enabling Switchable Passing Orders for More Efficient Multi-Agent Path Finding Plan Execution

Yifan Su, Rishi Veerapaneni, Jiaoyang Li

What Makes Good Collaborative Views? Contrastive Mutual Information Maximization for Multi-Agent Perception

Wanfang Su, Lixing Chen, Yang Bai, Xi Lin, Gaolei Li

Learn to Follow: Decentralized Lifelong Multi-Agent Pathfinding via Planning and Learning

Alexey Skrynnik, Anton Andreychuk, Maria Nesterova, Konstantin Yakovlev, Aleksandr Panov

Decentralized Monte Carlo Tree Search for Partially Observable Multi-Agent Pathfinding

Alexey Skrynnik, Anton Andreychuk, Konstantin Yakovlev, Aleksandr Panov

Minimum Coverage Sets for Training Robust Ad Hoc Teamwork Agents

Muhammad Rahman, Jiaxun Cui, Peter Stone

Adaptive Anytime Multi-Agent Path Finding Using Bandit-Based Large Neighborhood Search

Thomy Phan, Taoan Huang, Bistra Dilkina, Sven Koenig

PMAC: Personalized Multi-Agent Communication

Xiangrui Meng, Ying Tan

TAPE: Leveraging Agent Topology for Cooperative Multi-Agent Policy Gradient

Xingzhou Lou, Junge Zhang, Timothy J. Norman, Kaiqi Huang, Yali Du

Imagine, Initialize, and Explore: An Effective Exploration Method in Multi-Agent Reinforcement Learning

Zeyang Liu, Lipeng Wan, Xinrui Yang, Zhuoran Chen, Xingyu Chen

Decentralized Gradient-Free Methods for Stochastic Non-smooth Non-convex Optimization

Zhenwei Lin, Jingfan Xia, Qi Deng, Luo Luo

Transition-Informed Reinforcement Learning for Large-Scale Stackelberg Mean-Field Games

Pengdeng Li, Runsheng Yu, Xinrun Wang, Bo An

ConcaveQ: Non-monotonic Value Function Factorization via Concave Representations in Deep Multi-Agent Reinforcement Learning

Huiqun Li, Hanhan Zhou, Yifei Zou, Dongxiao Yu, Tian Lan

Optimistic Value Instructors for Cooperative Multi-Agent Reinforcement Learning

CHAO LI, Yupeng Zhang, Jianqi Wang, Yujing Hu, Shaokang Dong

Settling Decentralized Multi-Agent Coordinated Exploration by Novelty Sharing

Haobin Jiang, Ziluo Ding, Zongqing Lu

Stability of Multi-Agent Learning in Competitive Networks: Delaying the Onset of Chaos

Aamal Hussain, Francesco Belardinelli

Learning in Online Principal-Agent Interactions: The Power of Menus

Minbiao Han, Michael Albert, Haifeng Xu

Foundations of Reactive Synthesis for Declarative Process Specifications

Luca Geatti, Marco Montali, Andrey Rivkin

Factored Online Planning in Many-Agent POMDPs

Maris F. L. Galesloot, Thiago D. Simão, Sebastian Junges, Nils Jansen

Memory Asymmetry Creates Heteroclinic Orbits to Nash Equilibrium in Learning in Zero-Sum Games

Yuma Fujimoto, Kaito Ariu, Kenshi Abe

The Irrelevance of Influencers: Information Diffusion with Re-Activation and Immunity Lasts Exponentially Long on Social Network Models

Tobias Friedrich, Andreas Göbel, Nicolas Klodt, Martin S. Krejca, Marcus Pappik

Exact Algorithms and Lowerbounds for Multiagent Path Finding: Power of Treelike Topology

Foivos Fioravantes, Dusan Knop, Jan Matyáš Křištan, Nikolaos Melissinos, Michal Opler

Learning Multi-Object Positional Relationships via Emergent Communication

Yicheng Feng, Boshi An, Zongqing Lu

Situation-Dependent Causal Influence-Based Cooperative Multi-Agent Reinforcement Learning

Xiao Du, Yutong Ye, Pengyu Zhang, Yaning Yang, Mingsong Chen

Expressive Multi-Agent Communication via Identity-Aware Learning

Wei Du, Shifei Ding, Lili Guo, Jian Zhang, Ling Ding

Learning Efficient and Robust Multi-Agent Communication via Graph Information Bottleneck

Shifei Ding, Wei Du, Ling Ding, Lili Guo, Jian Zhang

STAS: Spatial-Temporal Return Decomposition for Solving Sparse Rewards Problems in Multi-agent Reinforcement Learning

Sirui Chen, Zhaowei Zhang, Yaodong Yang, Yali Du

RGMComm: Return Gap Minimization via Discrete Communications in Multi-Agent Reinforcement Learning

Jingdi Chen, Tian Lan, Carlee Joe-Wong

On Alternating-Time Temporal Logic, Hyperproperties, and Strategy Sharing

Raven Beutner, Bernd Finkbeiner

Natural Strategic Ability in Stochastic Multi-Agent Systems

Raphaël Berthon, Joost-Pieter Katoen, Munyque Mittelmann, Aniello Murano

Cautiously-Optimistic Knowledge Sharing for Cooperative Multi-Agent Reinforcement Learning

Yanwen Ba, Xuan Liu, Xinning Chen, Hao Wang, Yang Xu

Improved Anonymous Multi-Agent Path Finding Algorithm

Zain Alabedeen Ali, Konstantin Yakovlev

Probabilistic Neural Circuits

Pedro Zuidberg Dos Martires

Generalization Analysis of Machine Learning Algorithms via the Worst-Case Data-Generating Probability Measure

Xinying Zou, Samir M. Perlaza, Iñaki Esnaola, Eitan Altman

Coverage-Guaranteed Prediction Sets for Out-of-Distribution Data

Xin Zou, Weiwei Liu

Dirichlet-Based Prediction Calibration for Learning with Noisy Labels

Chen-Chen Zong, Ye-Wen Wang, Ming-Kun Xie, Sheng-jun Huang

Patch-Aware Sample Selection for Efficient Masked Image Modeling

Zhengyang Zhuge, Jiaxing Wang, Yong Li, Yongjun Bao, Peisong Wang

DS-AL: A Dual-Stream Analytic Learning for Exemplar-Free Class-Incremental Learning

HUIPING ZHUANG, Run He, Kai Tong, Ziqian Zeng, Cen Chen

MFABA: A More Faithful and Accelerated Boundary-Based Attribution Method for Deep Neural Networks

Zhiyu Zhu, Huaming Chen, Jiayu Zhang, Xinyi Wang, Zhibo Jin

Robust Node Classification on Graph Data with Graph and Label Noise

Yonghua Zhu, Lei Feng, Zhenyun Deng, Yang Chen, Robert Amor

Detection and Defense of Unlearnable Examples

Yifan Zhu, Lijia Yu, Xiao-Shan Gao

Decoding Global Preferences: Temporal and Cooperative Dependency Modeling in Multi-Agent Preference-Based Reinforcement Learning

Tianchen Zhu, Yue Qiu, Haoyi Zhou, Jianxin Li

Double Buffers CEM-TD3: More Efficient Evolution and Richer Exploration

Sheng Zhu, Chun Shen, Shuai Lu, Junhong Wu, Daolong An

Every Node Is Different: Dynamically Fusing Self-Supervised Tasks for Attributed Graph Clustering

Pengfei Zhu, Qian Wang, Yu Wang, Jialu Li, Qinghua Hu

Contrastive Balancing Representation Learning for Heterogeneous Dose-Response Curves Estimation

Minqin Zhu, Anpeng Wu, Haoxuan Li, Ruoxuan Xiong, Bo Li

Towards the Disappearing Truth: Fine-Grained Joint Causal Influences Learning with Hidden Variable-Driven Causal Hypergraphs in Time Series

Kun Zhu, Chunhui Zhao

Adaptive Meta-Learning Probabilistic Inference Framework for Long Sequence Prediction

Jianping Zhu, Xin Guo, Yang Chen, Yao Yang, Wenbo Li

Abstract and Explore: A Novel Behavioral Metric with Cyclic Dynamics in Reinforcement Learning

Anjie Zhu, Peng-Fei Zhang, Ruihong Qiu, Zetao Zheng, Zi Huang

Federated Label-Noise Learning with Local Diversity Product Regularization

Xiaochen Zhou, Xudong Wang

Generalizable Task Representation Learning for Offline Meta-Reinforcement Learning with Data Limitations

Renzhe Zhou, Chen-Xiao Gao, Zongzhang Zhang, Yang Yu

On the Robustness of Neural-Enhanced Video Streaming against Adversarial Attacks

Qihua ZHOU, Jingcai Guo, Song Guo, Ruibin Li, Jie Zhang

Token-Level Contrastive Learning with Modality-Aware Prompting for Multimodal Intent Recognition

Qianrui Zhou, Hua Xu, Hao Li, Hanlei Zhang, Xiaohan Zhang

Explaining Generalization Power of a DNN Using Interactive Concepts

Huilin Zhou, Hao Zhang, Huiqi Deng, Dongrui Liu, Wen Shen

Cycle Self-Refinement for Multi-Source Domain Adaptation

Chaoyang Zhou, Zengmao Wang, Bo Du, Yong Luo

PreRoutGNN for Timing Prediction with Order Preserving Partition: Global Circuit Pre-training, Local Delay Learning and Attentional Cell Modeling

Ruizhe Zhong, Junjie Ye, Zhentao Tang, Shixiong Kai, Mingxuan Yuan

No Prior Mask: Eliminate Redundant Action for Deep Reinforcement Learning

Dianyu Zhong, Yiqin Yang, Qianchuan Zhao

Knowledge-Aware Parameter Coaching for Personalized Federated Learning

Mingjian Zhi, Yuanguo Bi, Wenchao Xu, Haozhao Wang, Tianao Xiang

Confusing Pair Correction Based on Category Prototype for Domain Adaptation under Noisy Environments

Churan Zhi, Junbao Zhuo, Shuhui Wang

DCLP: Neural Architecture Predictor with Curriculum Contrastive Learning

Shenghe Zheng, Hongzhi Wang, Tianyu Mu

A Twist for Graph Classification: Optimizing Causal Information Flow in Graph Neural Networks

Zhe Zhao, Pengkun Wang, Haibin Wen, Yudong Zhang, Zhengyang Zhou

CcDPM: A Continuous Conditional Diffusion Probabilistic Model for Inverse Design

Yanxuan Zhao, Peng Zhang, Guopeng Sun, Zhigong Yang, Jianqiang Chen

Domain Invariant Learning for Gaussian Processes and Bayesian Exploration

Xilong Zhao, Siyuan Bian, Yaoyun Zhang, Yuliang Zhang, Qinying Gu

Embedded Feature Selection on Graph-Based Multi-View Clustering

Wenhui Zhao, Guangfei Li, Haizhou Yang, Quanxue Gao, Qianqian Wang

Robust Nonparametric Regression under Poisoning Attack

Puning Zhao, Zhiguo Wan

From GARCH to Neural Network for Volatility Forecast

Pengfei Zhao, Haoren Zhu, Wilfred Siu Hung NG, Dik Lun Lee

Robust Visual Recognition with Class-Imbalanced Open-World Noisy Data

Na Zhao, Gim Hee Lee

Learning Visual Abstract Reasoning through Dual-Stream Networks

KAI ZHAO, Chang Xu, Bailu Si

Dynamic Reactive Spiking Graph Neural Network

Han Zhao, Xu Yang, Cheng Deng, Junchi Yan

Symmetric Self-Paced Learning for Domain Generalization

Di Zhao, Yun Sing Koh, Gillian Dobbie, Hongsheng Hu, Philippe Fournier-Viger

Towards a Theoretical Understanding of Why Local Search Works for Clustering with Fair-Center Representation

Zhen Zhang, Junfeng Yang, Limei Liu, Xuesong Xu, Guozhen Rong

An Implicit Trust Region Approach to Behavior Regularized Offline Reinforcement Learning

Zhe Zhang, Xiaoyang Tan

Cached Transformers: Improving Transformers with Differentiable Memory Cachde

Zhaoyang Zhang, Wenqi Shao, Yixiao Ge, Xiaogang Wang, Jinwei Gu

Enhancing Representation of Spiking Neural Networks via Similarity-Sensitive Contrastive Learning

Yuhan Zhang, Xiaode Liu, Yuanpei Chen, Weihang Peng, Yufei Guo

Mitigating Label Bias in Machine Learning: Fairness through Confident Learning

YIXUAN ZHANG, Boyu Li, Zenan Ling, Feng Zhou

A Perspective of Q-value Estimation on Offline-to-Online Reinforcement Learning

Yinmin Zhang, Jie Liu, Chuming Li, Yazhe Niu, Yaodong Yang

Learning Multi-Task Sparse Representation Based on Fisher Information

Yayu Zhang, Yuhua Qian, Guoshuai Ma, Keyin Zheng, Guoqing Liu

Class-Attribute Priors: Adapting Optimization to Heterogeneity and Fairness Objective

Xuechen Zhang, Mingchen Li, Jiasi Chen, CHRISTOS THRAMPOULIDIS, Samet Oymak

Low Category Uncertainty and High Training Potential Instance Learning for Unsupervised Domain Adaptation

Xinyu Zhang, Meng Kang, Shuai Lu

From Toxic to Trustworthy: Using Self-Distillation and Semi-supervised Methods to Refine Neural Networks

Xianda Zhang, Baolin Zheng, Jianbao Hu, Chengyang Li, Xiaoying Bai

Gaussian Process Neural Additive Models

Wei Zhang, Brian Barr, John Paisley

One Step Closer to Unbiased Aleatoric Uncertainty Estimation

Wang Zhang, Ziwen Martin Ma, Subhro Das, Tsui-Wei Lily Weng, Alexandre Megretski

Learning with Noisy Labels Using Hyperspherical Margin Weighting

Shuo Zhang, Yuwen Li, Zhongyu Wang, Jianqing Li, Chengyu Liu

TC-LIF: A Two-Compartment Spiking Neuron Model for Long-Term Sequential Modelling

Shimin Zhang, Qu Yang, Chenxiang Ma, Jibin Wu, Haizhou Li

Reviewing the Forgotten Classes for Domain Adaptation of Black-Box Predictors

Shaojie Zhang, Chun Shen, Shuai Lu, Zeyu Zhang

Analyzing Generalization in Policy Networks: A Case Study with the Double-Integrator System

Ruining Zhang, Haoran Han, Maolong Lv, Qisong Yang, Jian Cheng

Efficient Deweahter Mixture-of-Experts with Uncertainty-Aware Feature-Wise Linear Modulation

Rongyu Zhang, Yulin Luo, Jiaming Liu, Huanrui Yang, Zhen Dong

A Learnable Discrete-Prior Fusion Autoencoder with Contrastive Learning for Tabular Data Synthesis

Rongchao Zhang, Yiwei Lou, Dexuan Xu, Yongzhi Cao, Hanpin Wang

United We Stand: Accelerating Privacy-Preserving Neural Inference by Conjunctive Optimization with Interleaved Nexus

Qiao Zhang, Tao Xiang, Chunsheng Xin, Hongyi Wu

Multi-Label Supervised Contrastive Learning

Pingyue Zhang, Mengyue Wu

Reinforced Adaptive Knowledge Learning for Multimodal Fake News Detection

Litian Zhang, Xiaoming Zhang, Ziyi Zhou, Feiran Huang, Chaozhuo Li

FedTGP: Trainable Global Prototypes with Adaptive-Margin-Enhanced Contrastive Learning for Data and Model Heterogeneity in Federated Learning

Jianqing Zhang, Yang Liu, Yang Hua, Jian Cao

Memory-Efficient Reversible Spiking Neural Networks

Hong Zhang, Yu Zhang

HONGAT: Graph Attention Networks in the Presence of High-Order Neighbors

Heng-Kai Zhang, Yi-Ge Zhang, Zhi Zhou, Yu-feng Li

Exponential Hardness of Optimization from the Locality in Quantum Neural Networks

Hao-Kai Zhang, Chengkai Zhu, Geng Liu, Xin Wang

Coupled Confusion Correction: Learning from Crowds with Sparse Annotations

Hansong Zhang, Shikun Li, Dan Zeng, Chenggang Yan, Shiming Ge