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AAMAS 2025

A*

International Conference on Autonomous Agents and Multiagent Systems

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480
accepted papers
445
authors
May 19-23, 2025
dates
USA
location

480 / 480 papers

  1. 1
    (Submodular) Hedonic Games with Common Ranking Property
    Bugra Çaskurlu
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  2. 2
    [COMP24] The Automated Negotiating Agents Competition (ANAC) 2024 Challenges and Results
    Reyhan Aydogan
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  3. 3
    A Hypothesis-Driven Approach to Explainable Goal Recognition
    Abeer Alshehri
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  4. 4
    A JAX-Accelerated Simulation Framework for Multi-Agent Energy Management in Energy Communities
    Hicham Azmani
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  5. 5
    A Minimalist Approach to Augmentation-based Self-supervised Representation Learning for On-policy Reinforcement Learning
    Nasik Muhammad Nafi
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  6. 6
    A Minimax Approach to Ad Hoc Teamwork
    Victor Villin
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  7. 7
    A Scoresheet for Explainable AI
    Michael Winikoff
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  8. 8
    A Simple Integration of Epistemic Logic and Reinforcement Learning
    Thorsten Engesser
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  9. 9
    A summary of: Tackling School Segregation with Transportation Network Interventions - An Agent-Based Modelling Approach
    Dimitris Michailidis
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  10. 10
    A View of the Certainty-Equivalence Method for PAC RL as an Application of the Trajectory Tree Method
    Shivaram Kalyanakrishnan
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  11. 11
    ACORN: Acyclic Coordination with Reachability Network to Reduce Communication Redundancy in Multi-Agent Systems
    Yi Xie
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  12. 12
    Action-Dependent Optimality-Preserving Reward Shaping
    Grant C. Forbes
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  13. 13
    AdaCred: Adaptive Causal Decision Transformers with Feature Crediting
    Hemant Kumawat
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  14. 14
    ADAGE: A Generic Two-layer Framework for Adaptive Agent based Modelling
    Benjamin Patrick Evans
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  15. 15
    Adapting Beyond the Depth Limit: Counter Strategies in Large Imperfect Information Games
    David Milec
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  16. 16
    Adaptive Bi-Level Multi-Robot Task Allocation and Learning under Uncertainty with Temporal Logic Constraints
    Xiaoshan Lin
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  17. 17
    Adaptive Budget Optimization for Multichannel Advertising Using Combinatorial Bandits
    Briti Gangopadhyay
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  18. 18
    Adaptive Episode Length Adjustment for Multi-agent Reinforcement Learning
    Byunghyun Yoo
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  19. 19
    Adaptive Microtolling in Competitive Online Congestion Games via Multiagent Reinforcement Learning
    Behrad Koohy
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  20. 20
    Adaptive Multi-Round Influence Maximization with Limited Information
    Vincenzo Auletta
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  21. 21
    Adaptive Offline Data Replay in Offline-to-Online Reinforcement Learning
    Xu Liu
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  22. 22
    Agent-Based Analysis of Green Disclosure Policies and Their Market-Wide Impact on Firm Behavior
    Lingxiao Zhao
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  23. 23
    Agent-based Modeling and Simulation of Ambiguity in Catastrophe Insurance Markets
    Yu Bi
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  24. 24
    Agent-Based Modeling of Smart Sustainable Mobility Services, Markets, and Policy
    Janik Muires
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  25. 25
    Agential AI for Integrated Continual Learning, Deliberative Behavior, and Comprehensible Models
    Zeki Doruk Erden
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  26. 26
    Agreement Games in Multi-Agent Systems
    Davide Catta
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  27. 27
    Algorithmically Fair Maximization of Multiple Submodular Objective Functions
    Georgios Amanatidis
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  28. 28
    AlphaZeroES: Direct Score Maximization Outperforms Planning Loss Minimization
    Carlos Martin
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  29. 29
    Alternating-time Temporal Logic with Stochastic Abilities
    Gabriel Ballot
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  30. 30
    An AI-Driven Card Playing Robot: An Empirical Study on Communicative Style and Embodiment with Elderly Adults
    Michael Banck
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  31. 31
    An Extended Benchmarking of Multi-Agent Reinforcement Learning Algorithms in Complex Fully Cooperative Tasks
    George Papadopoulos
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  32. 32
    An Improved Mechanism for Pricing Ride-Hailing Fares
    Marek Adamczyk
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  33. 33
    An Organizationally-Oriented Approach to Enhancing Explainability and Control in Multi-Agent Reinforcement Learning
    Julien Soulé
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  34. 34
    Anytime Fairness Guarantees in Stochastic Combinatorial MABs: A Novel Learning Framework
    Subham Pokhriyal
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  35. 35
    ApproxED: Approximate Exploitability Descent via Learned Best Responses
    Carlos Martin
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  36. 36
    Approximating One-Sided and Two-Sided Nash Social Welfare With Capacities
    Salil Gokhale
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  37. 37
    Approximation Algorithms for Connected Maximum Coverage
    Gianlorenzo D'Angelo
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  38. 38
    Approximation Ratio for Preference Aggregation Using Tree CP-Nets
    Abu Mohammad Hammad Ali
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  39. 39
    Artificial Agents Mitigate The Punishment Dilemma Of Indirect Reciprocity
    Alexandre S. Pires
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  40. 40
    Asymptotic Existence of Class Envy-free Matchings
    Tomohiko Yokoyama
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  41. 41
    Asynchronous Cooperative Multi-Agent Reinforcement Learning with Limited Communication
    Sydney Dolan
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  42. 42
    Automatic Verification of Linear Integer Planning Programs via Forgetting in LIAUPF
    Liangda Fang
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  43. 43
    Automating Curriculum Learning for Reinforcement Learning using a Skill-Based Bayesian Network
    Vincent Hsiao
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  44. 44
    Azorus: Commitments over Protocols for BDI Agents
    Amit K. Chopra
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  45. 45
    Balancing Fairness and Efficiency in the Allocation of Indivisible Goods
    Karen Frilya Celine
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  46. 46
    Bayesian Collaborative Bandits with Thompson Sampling for Improved Outreach in Maternal Health
    Arpan Dasgupta
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  47. 47
    Beyond Goal Recognition: A Reinforcement Learning-based Approach to Inferring Agent Behaviour
    Sheryl Mantik
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  48. 48
    Beyond the Echo Chamber: Modelling Open-Mindedness in Citizens' Assemblies
    Jake Barrett
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  49. 49
    Beyond Words: Integrating Personality Traits and Context-Driven Gestures in Human-Robot Interactions
    Tahsin Tariq Banna
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  50. 50
    Bi-Level Reinforcement Learning for Multi-Robot Systems
    Arjun Prakash
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