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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence, 35 /

No. 13: AAAI-21 Technical Tracks 13

AAAI Technical Track on Multiagent Systems

  • Resilient Multi-Agent Reinforcement Learning with Adversarial Value Decomposition

    Thomy Phan, Lenz Belzner, Thomas Gabor, Andreas Sedlmeier, Fabian Ritz, Claudia Linnhoff-Popien

    11308-11316

    PDF
  • Coordination Between Individual Agents in Multi-Agent Reinforcement Learning

    Yang Zhang, Qingyu Yang, Dou An, Chengwei Zhang

    11387-11394

    PDF
  • Efficient Querying for Cooperative Probabilistic Commitments

    Qi Zhang, Edmund H. Durfee, Satinder Singh

    11378-11386

    PDF
  • Maintenance of Social Commitments in Multiagent Systems

    Pankaj Telang, Munindar P. Singh, Neil Yorke-Smith

    11369-11377

    PDF
  • Contract-based Inter-user Usage Coordination in Free-floating Car Sharing

    Kentaro Takahira, Shigeo Matsubara

    11361-11368

    PDF
  • Value-Decomposition Multi-Agent Actor-Critics

    Jianyu Su, Stephen Adams, Peter Beling

    11352-11360

    PDF
  • Evolutionary Game Theory Squared: Evolving Agents in Endogenously Evolving Zero-Sum Games

    Stratis Skoulakis, Tanner Fiez, Ryann Sim, Georgios Piliouras, Lillian Ratliff

    11343-11351

    PDF
  • Synchronous Dynamical Systems on Directed Acyclic Graphs: Complexity and Algorithms

    Daniel J. Rosenkrantz, Madhav Marathe, S. S. Ravi, Richard E. Stearns

    11334-11342

    PDF
  • Newton Optimization on Helmholtz Decomposition for Continuous Games

    Giorgia Ramponi, Marcello Restelli

    11325-11333

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  • Anytime Heuristic and Monte Carlo Methods for Large-Scale Simultaneous Coalition Structure Generation and Assignment

    Fredrik Präntare, Herman Appelgren, Fredrik Heintz

    11317-11324

    PDF
  • Time-Independent Planning for Multiple Moving Agents

    Keisuke Okumura, Yasumasa Tamura, Xavier Défago

    11299-11307

    PDF
  • Expected Value of Communication for Planning in Ad Hoc Teamwork

    William Macke, Reuth Mirsky, Peter Stone

    11290-11298

    PDF
  • Dec-SGTS: Decentralized Sub-Goal Tree Search for Multi-Agent Coordination

    Minglong Li, Zhongxuan Cai, Wenjing Yang, Lixia Wu, Yinghui Xu, Ji Wang

    11282-11289

    PDF
  • Lifelong Multi-Agent Path Finding in Large-Scale Warehouses

    Jiaoyang Li, Andrew Tinka, Scott Kiesel, Joseph W. Durham, T. K. Satish Kumar, Sven Koenig

    11272-11281

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  • Exploration-Exploitation in Multi-Agent Learning: Catastrophe Theory Meets Game Theory

    Stefanos Leonardos, Georgios Piliouras

    11263-11271

    PDF
  • Improving Continuous-time Conflict Based Search

    Anton Andreychuk,Konstantin Yakovlev,Eli Boyarski,Roni Stern

    11220-11227

    PDF
  • The Influence of Memory in Multi-Agent Consensus

    David Kohan Marzagão, Luciana Basualdo Bonatto, Tiago Madeira, Marcelo Matheus Gauy, Peter McBurney

    11254-11262

    PDF
  • Learning to Resolve Conflicts for Multi-Agent Path Finding with Conflict-Based Search

    Taoan Huang, Sven Koenig, Bistra Dilkina

    11246-11253

    PDF
  • Scalable and Safe Multi-Agent Motion Planning with Nonlinear Dynamics and Bounded Disturbances

    Jingkai Chen, Jiaoyang Li, Chuchu Fan, Brian C. Williams

    11237-11245

    PDF
  • Inference-Based Deterministic Messaging For Multi-Agent Communication

    Varun Bhatt, Michael Buro

    11228-11236

    PDF

AAAI Technical Track on Philosophy and Ethics of AI

  • Decision-Guided Weighted Automata Extraction from Recurrent Neural Networks

    Xiyue Zhang, Xiaoning Du, Xiaofei Xie, Lei Ma, Yang Liu, Meng Sun

    11699-11707

    PDF
  • Fair Influence Maximization: a Welfare Optimization Approach

    Aida Rahmattalabi, Shahin Jabbari, Himabindu Lakkaraju, Phebe Vayanos, Max Izenberg, Ryan Brown, Eric Rice, Milind Tambe

    11630-11638

    PDF
  • Explaining Convolutional Neural Networks through Attribution-Based Input Sampling and Block-Wise Feature Aggregation

    Sam Sattarzadeh, Mahesh Sudhakar, Anthony Lem, Shervin Mehryar, Konstantinos N Plataniotis, Jongseong Jang, Hyunwoo Kim, Yeonjeong Jeong, Sangmin Lee, Kyunghoon Bae

    11639-11647

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  • Exploring the Vulnerability of Deep Neural Networks: A Study of Parameter Corruption

    Xu Sun, Zhiyuan Zhang, Xuancheng Ren, Ruixuan Luo, Liangyou Li

    11648-11656

    PDF
  • Ethically Compliant Sequential Decision Making

    Justin Svegliato, Samer B. Nashed, Shlomo Zilberstein

    11657-11665

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  • Improving Robustness to Model Inversion Attacks via Mutual Information Regularization

    Tianhao Wang, Yuheng Zhang, Ruoxi Jia

    11666-11673

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  • Tightening Robustness Verification of Convolutional Neural Networks with Fine-Grained Linear Approximation

    Yiting Wu, Min Zhang

    11674-11681

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  • Invertible Concept-based Explanations for CNN Models with Non-negative Concept Activation Vectors

    Ruihan Zhang, Prashan Madumal, Tim Miller, Krista A. Ehinger, Benjamin I. P. Rubinstein

    11682-11690

    PDF
  • i-Algebra: Towards Interactive Interpretability of Deep Neural Networks

    Xinyang Zhang, Ren Pang, Shouling Ji, Fenglong Ma, Ting Wang

    11691-11698

    PDF
  • Differentially Private Clustering via Maximum Coverage

    Matthew Jones, Huy L. Nguyen, Thy D Nguyen

    11555-11563

    PDF
  • Comprehension and Knowledge

    Pavel Naumov, Kevin Ros

    11622-11629

    PDF
  • Ethical Dilemmas in Strategic Games

    Pavel Naumov, Rui-Jie Yew

    11613-11621

    PDF
  • Interpreting Deep Neural Networks with Relative Sectional Propagation by Analyzing Comparative Gradients and Hostile Activations

    Woo-Jeoung Nam, Jaesik Choi, Seong-Whan Lee

    11604-11612

    PDF
  • Outlier Impact Characterization for Time Series Data

    Jianbo Li, Lecheng Zheng, Yada Zhu, Jingrui He

    11595-11603

    PDF
  • How RL Agents Behave When Their Actions Are Modified

    Eric D. Langlois, Tom Everitt

    11586-11594

    PDF
  • On Generating Plausible Counterfactual and Semi-Factual Explanations for Deep Learning

    Eoin M. Kenny, Mark T Keane

    11575-11585

    PDF
  • Ordered Counterfactual Explanation by Mixed-Integer Linear Optimization

    Kentaro Kanamori, Takuya Takagi, Ken Kobayashi, Yuichi Ike, Kento Uemura, Hiroki Arimura

    11564-11574

    PDF
  • Visualization of Supervised and Self-Supervised Neural Networks via Attribution Guided Factorization

    Shir Gur, Ameen Ali, Lior Wolf

    11545-11554

    PDF
  • Beyond Class-Conditional Assumption: A Primary Attempt to Combat Instance-Dependent Label Noise

    Pengfei Chen, Junjie Ye, Guangyong Chen, Jingwei Zhao, Pheng-Ann Heng

    11442-11450

    PDF
  • Robustness of Accuracy Metric and its Inspirations in Learning with Noisy Labels

    Pengfei Chen, Junjie Ye, Guangyong Chen, Jingwei Zhao, Pheng-Ann Heng

    11451-11461

    PDF
  • A Unified Taylor Framework for Revisiting Attribution Methods

    Huiqi Deng, Na Zou, Mengnan Du, Weifu Chen, Guocan Feng, Xia Hu

    11462-11469

    PDF
  • Verifiable Machine Ethics in Changing Contexts

    Louise A. Dennis, Martin Mose Bentzen, Felix Lindner, Michael Fisher

    11470-11478

    PDF
  • Epistemic Logic of Know-Who

    Sophia Epstein, Pavel Naumov

    11479-11486

    PDF
  • Agent Incentives: A Causal Perspective

    Tom Everitt, Ryan Carey, Eric D. Langlois, Pedro A. Ortega, Shane Legg

    11487-11495

    PDF
  • Individual Fairness in Kidney Exchange Programs

    Golnoosh Farnadi, William St-Arnaud, Behrouz Babaki, Margarida Carvalho

    11496-11505

    PDF
  • Fair Representations by Compression

    Xavier Gitiaux, Huzefa Rangwala

    11506-11515

    PDF
  • Amnesiac Machine Learning

    Laura Graves, Vineel Nagisetty, Vijay Ganesh

    11516-11524

    PDF
  • On the Verification of Neural ODEs with Stochastic Guarantees

    Sophie Grunbacher, Ramin Hasani, Mathias Lechner, Jacek Cyranka, Scott A. Smolka, Radu Grosu

    11525-11535

    PDF
  • PenDer: Incorporating Shape Constraints via Penalized Derivatives

    Akhil Gupta, Lavanya Marla, Ruoyu Sun, Naman Shukla, Arinbjörn Kolbeinsson

    11536-11544

    PDF
  • Explaining A Black-box By Using A Deep Variational Information Bottleneck Approach

    Seojin Bang, Pengtao Xie, Heewook Lee, Wei Wu, Eric Xing

    11396-11404

    PDF
  • FIMAP: Feature Importance by Minimal Adversarial Perturbation

    Matt Chapman-Rounds, Umang Bhatt, Erik Pazos, Marc-Andre Schulz, Konstantinos Georgatzis

    11433-11441

    PDF
  • Bayes-TrEx: a Bayesian Sampling Approach to Model Transparency by Example

    Serena Booth, Yilun Zhou, Ankit Shah, Julie Shah

    11423-11432

    PDF
  • TripleTree: A Versatile Interpretable Representation of Black Box Agents and their Environments

    Tom Bewley, Jonathan Lawry

    11415-11422

    PDF
  • Is the Most Accurate AI the Best Teammate? Optimizing AI for Teamwork

    Gagan Bansal, Besmira Nushi, Ece Kamar, Eric Horvitz, Daniel S. Weld

    11405-11414

    PDF

AAAI Technical Track on Planning, Routing, and Scheduling

  • Multi-Decoder Attention Model with Embedding Glimpse for Solving Vehicle Routing Problems

    Liang Xin, Wen Song, Zhiguang Cao, Jie Zhang

    12042-12049

    PDF
  • Competitive Analysis for Two-Level Ski-Rental Problem

    Binghan Wu, Wei Bao, Dong Yuan

    12034-12041

    PDF
  • Asking the Right Questions: Learning Interpretable Action Models Through Query Answering

    Pulkit Verma, Shashank Rao Marpally, Siddharth Srivastava

    12024-12033

    PDF
  • Dynamic Automaton-Guided Reward Shaping for Monte Carlo Tree Search

    Alvaro Velasquez, Brett Bissey, Lior Barak, Andre Beckus, Ismail Alkhouri, Daniel Melcer, George Atia

    12015-12023

    PDF
  • On the Optimal Efficiency of A* with Dominance Pruning

    Álvaro Torralba

    12007-12014

    PDF
  • Faster Stackelberg Planning via Symbolic Search and Information Sharing

    Álvaro Torralba, Patrick Speicher, Robert Künnemann, Marcel Steinmetz, Jörg Hoffmann

    11998-12006

    PDF
  • A Complexity-theoretic Analysis of Green Pickup-and-Delivery Problems

    Xing Tan, Jimmy Xiangji Huang

    11990-11997

    PDF
  • Online Action Recognition

    Alejandro Suárez-Hernández, Javier Segovia-Aguas, Carme Torras, Guillem Alenyà

    11981-11989

    PDF
  • Improved POMDP Tree Search Planning with Prioritized Action Branching

    John Mern, Anil Yildiz, Lawrence Bush, Tapan Mukerji, Mykel J. Kochenderfer

    11888-11894

    PDF
  • Bayesian Optimized Monte Carlo Planning

    John Mern, Anil Yildiz, Zachary Sunberg, Tapan Mukerji, Mykel J. Kochenderfer

    11880-11887

    PDF
  • Synthesis of Search Heuristics for Temporal Planning via Reinforcement Learning

    Andrea Micheli, Alessandro Valentini

    11895-11902

    PDF
  • Revealing Hidden Preconditions and Effects of Compound HTN Planning Tasks – A Complexity Analysis

    Conny Olz, Susanne Biundo, Pascal Bercher

    11903-11912

    PDF
  • Faster and Better Simple Temporal Problems

    Dario Ostuni, Alice Raffaele, Romeo Rizzi, Matteo Zavatteri

    11913-11920

    PDF
  • Latent Independent Excitation for Generalizable Sensor-based Cross-Person Activity Recognition

    Hangwei Qian, Sinno Jialin Pan, Chunyan Miao

    11921-11929

    PDF
  • Minimax Regret Optimisation for Robust Planning in Uncertain Markov Decision Processes

    Marc Rigter, Bruno Lacerda, Nick Hawes

    11930-11938

    PDF
  • An LP-Based Approach for Goal Recognition as Planning

    Luísa R. A. Santos, Felipe Meneguzzi, Ramon Fraga Pereira, André Grahl Pereira

    11939-11946

    PDF
  • Saturated Post-hoc Optimization for Classical Planning

    Jendrik Seipp, Thomas Keller, Malte Helmert

    11947-11953

    PDF
  • Improved Knowledge Modeling and Its Use for Signaling in Multi-Agent Planning with Partial Observability

    Shashank Shekhar, Ronen I. Brafman, Guy Shani

    11954-11961

    PDF
  • Planning with Learned Object Importance in Large Problem Instances using Graph Neural Networks

    Tom Silver, Rohan Chitnis, Aidan Curtis, Joshua B. Tenenbaum, Tomás Lozano-Pérez, Leslie Pack Kaelbling

    11962-11971

    PDF
  • Symbolic Search for Oversubscription Planning

    David Speck, Michael Katz

    11972-11980

    PDF
  • Progression Heuristics for Planning with Probabilistic LTL Constraints

    Ian Mallett, Sylvie Thiebaux, Felipe Trevizan

    11870-11879

    PDF
  • On-line Learning of Planning Domains from Sensor Data in PAL: Scaling up to Large State Spaces

    Leonardo Lamanna, Alfonso Emilio Gerevini, Alessandro Saetti, Luciano Serafini, Paolo Traverso

    11862-11869

    PDF
  • Branch and Price for Bus Driver Scheduling with Complex Break Constraints

    Lucas Kletzander, Nysret Musliu, Pascal Van Hentenryck

    11853-11861

    PDF
  • Bike-Repositioning Using Volunteers: Crowd Sourcing with Choice Restriction

    Jinjia Huang, Mabel C. Chou, Chung-Piaw Teo

    11844-11852

    PDF
  • Endomorphisms of Classical Planning Tasks

    Rostislav Horčík, Daniel Fišer

    11835-11843

    PDF
  • Landmark Generation in HTN Planning

    Daniel Höller, Pascal Bercher

    11826-11834

    PDF
  • Equitable Scheduling on a Single Machine

    Klaus Heeger, Dan Hermelin, George B. Mertzios, Hendrik Molter, Rolf Niedermeier, Dvir Shabtay

    11818-11825

    PDF
  • Revisiting Dominance Pruning in Decoupled Search

    Daniel Gnad

    11809-11817

    PDF
  • Constrained Risk-Averse Markov Decision Processes

    Mohamadreza Ahmadi, Ugo Rosolia, Michel D. Ingham, Richard M. Murray, Aaron D. Ames

    11718-11725

    PDF
  • Computing Plan-Length Bounds Using Lengths of Longest Paths

    Mohammad Abdulaziz,Dominik Berger

    11709-11717

    PDF
  • Contract Scheduling With Predictions

    Spyros Angelopoulos, Shahin Kamali

    11726-11733

    PDF
  • Responsibility Attribution in Parameterized Markovian Models

    Christel Baier, Florian Funke, Rupak Majumdar

    11734-11743

    PDF
  • Symbolic Search for Optimal Total-Order HTN Planning

    Gregor Behnke, David Speck

    11744-11754

    PDF
  • A Multivariate Complexity Analysis of the Material Consumption Scheduling Problem

    Matthias Bentert, Robert Bredereck, Péter Györgyi, Andrzej Kaczmarczyk, Rolf Niedermeier

    11755-11763

    PDF
  • General Policies, Representations, and Planning Width

    Blai Bonet, Hector Geffner

    11764-11773

    PDF
  • Successor Feature Sets: Generalizing Successor Representations Across Policies

    Kianté Brantley, Soroush Mehri, Geoff J. Gordon

    11774-11781

    PDF
  • GLIB: Efficient Exploration for Relational Model-Based Reinforcement Learning via Goal-Literal Babbling

    Rohan Chitnis, Tom Silver, Joshua B. Tenenbaum, Leslie Pack Kaelbling, Tomás Lozano-Pérez

    11782-11791

    PDF
  • Robust Finite-State Controllers for Uncertain POMDPs

    Murat Cubuktepe, Nils Jansen, Sebastian Junges, Ahmadreza Marandi, Marnix Suilen, Ufuk Topcu

    11792-11800

    PDF
  • Learning General Planning Policies from Small Examples Without Supervision

    Guillem Francès, Blai Bonet, Hector Geffner

    11801-11808

    PDF

AAAI Technical Track on Reasoning under Uncertainty

  • Bounding Causal Effects on Continuous Outcome

    Junzhe Zhang, Elias Bareinboim

    12207-12215

    PDF
  • Polynomial-Time Algorithms for Counting and Sampling Markov Equivalent DAGs

    Marcel Wienöbst, Max Bannach, Maciej Liskiewicz

    12198-12206

    PDF
  • Learning the Parameters of Bayesian Networks from Uncertain Data

    Segev Wasserkrug, Radu Marinescu, Sergey Zeltyn, Evgeny Shindin, Yishai A Feldman

    12190-12197

    PDF
  • Robust Contextual Bandits via Bootstrapping

    Qiao Tang, Hong Xie, Yunni Xia, Jia Lee, Qingsheng Zhu

    12182-12189

    PDF
  • Probabilistic Dependency Graphs

    Oliver Richardson, Joseph Y Halpern

    12174-12181

    PDF
  • Estimation of Spectral Risk Measures

    Ajay Kumar Pandey, Prashanth L.A., Sanjay P. Bhat

    12166-12173

    PDF
  • A New Bounding Scheme for Influence Diagrams

    Radu Marinescu, Junkyu Lee, Rina Dechter

    12158-12165

    PDF
  • Instrumental Variable-based Identification for Causal Effects using Covariate Information

    Yuta Kawakami

    12131-12138

    PDF
  • Submodel Decomposition Bounds for Influence Diagrams

    Junkyu Lee, Radu Marinescu, Rina Dechter

    12147-12157

    PDF
  • Learning Continuous High-Dimensional Models using Mutual Information and Copula Bayesian Networks

    Marvin Lasserre, Régis Lebrun, Pierre-Henri Wuillemin

    12139-12146

    PDF
  • Group Fairness by Probabilistic Modeling with Latent Fair Decisions

    YooJung Choi, Meihua Dang, Guy Van den Broeck

    12051-12059

    PDF
  • Relational Boosted Bandits

    Ashutosh Kakadiya, Sriraam Natarajan, Balaraman Ravindran

    12123-12130

    PDF
  • Estimating Identifiable Causal Effects through Double Machine Learning

    Yonghan Jung, Jin Tian, Elias Bareinboim

    12113-12122

    PDF
  • A Generative Adversarial Framework for Bounding Confounded Causal Effects

    Yaowei Hu, Yongkai Wu, Lu Zhang, Xintao Wu

    12104-12112

    PDF
  • High Dimensional Level Set Estimation with Bayesian Neural Network

    Huong Ha, Sunil Gupta, Santu Rana, Svetha Venkatesh

    12095-12103

    PDF
  • Scalable First-Order Methods for Robust MDPs

    Julien Grand-Clément, Christian Kroer

    12086-12094

    PDF
  • Uncertainty Quantification in CNN Through the Bootstrap of Convex Neural Networks

    Hongfei Du, Emre Barut, Fang Jin

    12078-12085

    PDF
  • Better Bounds on the Adaptivity Gap of Influence Maximization under Full-adoption Feedback

    Gianlorenzo D'Angelo, Debashmita Poddar, Cosimo Vinci

    12069-12077

    PDF
  • GO Hessian for Expectation-Based Objectives

    Yulai Cong, Miaoyun Zhao, Jianqiao Li, Junya Chen, Lawrence Carin

    12060-12068

    PDF

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