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All submissions will be rigorously peer-reviewed and evaluated on the basis of the overall quality of their technical contribution, taking into account criteria such as originality, significance, soundness, reproducibility, clarity, relevance to the conference, quality of presentation, as well as understanding and appropriate referencing of the state of the art.

The papers will be published under CC BY license.

Important Dates

  • Abstract submission: Oct 9, 2024
  • Paper submission: Oct 16, 2024
  • Rebuttal period: Nov 27 – Dec 4, 2024
  • Author notification: Dec 23, 2024
  • Camera-ready paper: Feb 7, 2025
  • Conference: May 19-23, 2025

All deadlines are at the end of the specified day, Anywhere on Earth (UTC-12).

For submission instructions, please see here.

For responses to questions frequently asked by authors who wish to submit to AAMAS, please visit this FAQ page.

Areas of Interest

We welcome the submission of technical papers describing significant and original research on all aspects of the theory and practice of autonomous agents and multiagent systems. If you are new to this community, then we encourage you to consult the proceedings of previous editions of the conference to fully appreciate the scope of AAMAS. At the time of submission, you will be asked to associate your paper with one of the following areas of interest:

  • Learning and Adaptation (LEARN)
  • Game Theory and Economic Paradigms (GTEP)
  • Coordination, Organizations, Institutions, Norms, and Ethics (COINE)
  • Search, Optimization, Planning, and Scheduling (SOPS)
  • Representation, Perception, and Reasoning (RPR)
  • Engineering and Analysis of Multiagent Systems (EMAS)
  • Modeling and Simulation of Societies (SIM)
  • Human-Agent Interaction (HAI)
  • Robotics and Control (ROBOT)
  • Innovative Applications (IA)

Additionally, AAMAS 2025 includes several special tracks.  You can find more information about these tracks here.

Learning and Adaptation (LEARN)

Area Chairs: Long Tran-Thanh, Bo An, Marc Lanctot, Chongjie Zhang, Jianye Hao, Haifeng Xu, Jakob Foerster

Topics

  • Reasoning and learning under uncertainty
  • Supervised learning
  • Unsupervised and representation learning
  • Reinforcement learning
  • Multiagent learning
  • Evolutionary algorithms
  • Learning agent capabilities
  • Learning agent-to-agent interactions
  • Human-in-the-loop learning
  • Agency and learning in large language models (LLMs)
  • Learning for value alignment and RLHF
  • Modeling and analysis of Generative AI agents
  • Few-shot learning
  • Distributionally-robust learning
  • Adversarial learning

Description: Autonomous Agents must sense, deliberate, act and communicate in potentially complex and uncertain environments. In addition, in many cases, they must interact with other agents and/or humans. Anticipating each situation and hardcoding the appropriate agent behavior becomes impossible as the complexity of the environment and interactions increase. As such, adaptivity and learning are key properties that imbue autonomy to agents operating and communicating in the real world. Papers in this area focus on all aspects of single agent and multiagent planning, learning and communication.

Game Theory and Economic Paradigms (GTEP)

Area Chairs: Reshef Meir, Nisarg Shah, Georgios Piliouras, Vasilis Gkatzelis, Rica Gonen

Topics:

  • Auctions and Mechanism Design
  • Bargaining and Negotiation
  • Behavioral Game Theory
  • Evolutionary Game Theory
  • Non-Cooperative Games: Equilibrium Concepts
  • Non-Cooperative Games: Computational Issues
  • Non-Cooperative Games: Theory and Applications
  • Voting and Preference Aggregation
  • Social Choice
  • Preference Aggregation and Value Alignment
  • Matching and Allocation
  • Coalition Formation
  • Cooperative Games

Description: This area encompasses research on cooperative and non-cooperative games, social choice, and mechanism design, specifically focusing on computational aspects such as algorithmic and complexity analysis for equilibrium computation and verification. The area also welcomes theoretical explorations and analysis related to game theory, mechanism and market design, and social choice. Submissions showcasing practical applications of game theory are also strongly encouraged.

Coordination, Organizations, Institutions, Norms, and Ethics (COINE)

Area Chairs: Felipe Meneguzzi, Pradeep Murukannaiah

Topics:

  • Coordination and teamwork
  • Social network analysis
  • Norms, normative systems
  • Organizations and institutions
  • Non-strategic coalition/team formation
  • Communication, including using natural language
  • Policy, regulation, and accountability
  • Trust and reputation
  • Ethical considerations, including privacy, safety, security, transparency
  • Agreement Technologies: Negotiation and Argumentations
  • Responsible socio-technical systems

Description: Research in agent and multiagent systems has a long history of developing techniques that balance agent autonomy, adaptation, and distributed social reasoning with system-level considerations such as organizational and institutional policy enforcement addressing safety, security and fairness considerations.  Teamwork and human-machine cooperation has an increased relevance with the transformation of our societies into socio-technical systems. We need to ensure transparency, foster trust, and ensure social reasoning conforms to societal norms and expectations. We also need to ensure human-machine and machine-machine cooperation is fostered responsibly, within an adequate accountability system and in alignment with the ethical values of individuals concerned.  We encourage the submission of papers that highlight the design, development, evaluation, simulation, and analysis of novel, innovative, and impactful research on issues related to the above topics.

Search, Optimization, Planning, and Scheduling (SOPS)

Area Chairs: William Yeoh, Sven Koenig

Topics

  • Single-agent planning and scheduling
  • Multiagent planning and scheduling
  • Decentralized planning and scheduling
  • Planning under uncertainty
  • Combinatorial optimization 
  • Constraint programming
  • Distributed constraint reasoning
  • Resource and task allocation
  • Non-strategic coalition formation

Description: This area includes theoretical or experimental contributions to search, optimization, planning, and scheduling in single- and multi-agent systems. Important subfields include decentralized planning, planning under uncertainty, combinatorial optimization, distributed constraint reasoning, resource and task allocation, and non-strategic coalition formation.  Machine learning approaches as well as foundation models for planning and scheduling are encouraged. Likewise, all approaches to single- and multi-agent planning, including motion and path planning, and their interplay with other agent components are relevant.

Representation, Perception, and Reasoning (RPR)

Area Chairs: Natasha Alechina, Aparna Taneja, Alessio Lomuscio

Topics

  • Computer vision
  • Representation learning and generative AI
  • Neurosymbolic approaches
  • Argumentation
  • Agent theories and models
  • Explainability
  • Logics for agent reasoning
  • Ontologies for agents
  • Reasoning about knowledge, beliefs, goals, actions, plans, and change in multiagent systems
  • Reasoning and problem solving in agent-based systems
  • Verification of agents and multiagent systems

Description: This area includes theoretical or experimental contributions to knowledge representation and reasoning in single-agent and multi-agent systems. Knowledge representation is to be understood broadly, ranging from theoretical contributions (e.g., epistemic, strategic, description, and other logics) to representation learning.  Moreover, representation and reasoning in complex settings often entails reasoning about sensing and perception.  Relevant  forms of reasoning include, for instance, automated reasoning and theorem proving approaches, verification-based approaches, as well as probabilistic reasoning and neurosymbolic approaches, as long as they are applied to, or motivated by reasoning about agents and/or multiagent systems. 

Engineering and Analysis of Multiagent Systems (EMAS)

Area Chairs: Viviana Mascardi, Daniela Briola

Topics:

  • Requirements and formal specification
  • Architecture and modeling
  • Formal verification and validation
  • Programming models and languages
  • Testing, maintenance, and evolution
  • Concurrency, fault tolerance, robustness, reliability, performance, and scalability
  • Sociotechnical systems, norms, and governance
  • Responsibility and accountability
  • Interoperability, business agreements, and interaction protocols
  • Declarative, Logic-based, and BDI-based agents
  • Engineering ethical agents
  • Engineering MAS-based simulations
  • Tools and testbeds
  • Technological paradigms, including microservices, the Web, the IoT, Cloud computing, distributed Ledgers, and Robotics
  • Middleware and platforms for MAS
  • Engineering learning agents
  • Usability
  • Applications, including Finance, Health, Agriculture, Autonomous Vehicles and Smart-*

Description: This area invites contributions that focus on general-purpose software abstractions and methodologies (including software systems) that advance the engineering of agents and multiagent systems. Contributions that demonstrate the benefit of such abstractions and methodologies for interesting application domains and other technological paradigms are also welcome. Naturally, the scope of this area spans the entire software engineering lifecycle — from requirements and verification to testing, validation, and evolution.

Modeling and Simulation of (Artificial) Societies (SIM)

Area Chairs: Ana Bazzan, Samarth Swarup

Topics

  • Analysis of agent-based simulations
  • Calibration methods for socio-demographic data
  • Agent-based models & Social Networks
  • Applications of agent-based simulations in social phenomena (polarization, inequality, etc.)
  • Emergent behavior
  • Engineering agent-based simulations 
  • Interactive simulation
  • Modeling for agent-based simulation
  • Simulation of complex systems
  • Simulation techniques, tools and platforms
  • Social simulation
  • Validation of social simulation systems

Description: Artificial societies are computer simulations or models that are created to emulate and research the behavior of intricate social systems. These societies simulate the interactions and dynamics of people, animals or other organisms to understand how individual behaviors lead to emergent structures and interactions. Agent-based models of artificial society provide a way to analyze the impact of regulations, incentives and other interventions that help to understand the complex dynamics of society as a whole. The area aims to find efficient solutions to model and simulate complex societal systems using agents-based models. Important application areas include ecology, biology, economics, transportation, management, organizational, and social sciences in general. In these areas, agent theories, metaphors, models, analysis, experimental designs, empirical studies, and methodological principles, all converge into simulation as a way of achieving explanations and predictions, exploration and testing of hypotheses, and better system designs.

Human-Agent Interaction (HAI)

Area Chairs: Michael Goodrich, Birgit Lugrin

Topics

  • Human-agent interaction
  • Agent-based analysis of human interactions
  • Socially interactive agents
  • Trust and explainability in human-agent interactions
  • Human-robot interaction and collaboration
  • Social robotics and social interactions
  • Mixed-initiative and shared autonomy in human-agent interactions
  • Groups of humans and agents
  • Agents models and architectures for interaction with humans
  • Designing for human-agent interaction
  • Virtual humans

Description:

Human interaction with artificially intelligent agents is becoming more commonplace, as such, developing and evaluating agents that can understand humans’ dynamics to support competent interaction. Significant challenges arise when transitioning from pure multiagent systems to hybrid systems that need to incorporate bi-directional human and agent interactions and sustain different competitive or collaborative situations. Agents need new models and architectures to better address the interaction with humans, including perception and recognition of humans’ internal states and activities at different levels, interaction modalities that support true coordination, and incorporation of human factors and ethics concerns. The design of human-agent interaction needs special concerns that combine requirements from the perspectives of both the agents and the humans. The interactive behavior of such agents can be inspired by human-human interaction and can, additionally, be embodied by virtual agents or robots to scaffold intuitive interaction.

Robotics and Control (ROBOT)

Area Chairs: Noa Agmon, Christopher Amato

Topics

  • Multi-robot coordination and collaboration 
  • Robot planning
  • Robot learning
  • Explainability, trust and ethics for robots
  • Knowledge representation and reasoning in robotic systems
  • Long-term (or lifelong) autonomy for robotic systems
  • Mapping, localization and exploration
  • Robot Modeling & Simulation
  • Manipulation and navigation
  • Networked systems and distributed robotics
  • Robot control
  • Robot perception and vision
  • Robots in adversarial settings
  • Swarm and collective behavior
  • Execution monitoring and failure recovery for robots

Description: Robotics is one of the most exciting fields in agent research. We invite papers that advance theory and/or application of single and multiple robots, with particular emphasis on solutions based on realistic assumptions typically encountered in robotic applications. All papers at the intersection of robotics and artificial intelligence (and agent research, specifically) are in the scope of the robotics area at AAMAS. 

Innovative Applications (IA)

Area Chairs: Thanh Nguyen, Pradeep Varakantham

Topics

  • Deployed or emerging applications of agent-based systems 
  • Realistic agent-based models of human organizations
  • Evaluation of the cognitive capabilities of agent-based systems
  • Integrated applications of agent-based and other technologies
  • Challenges and best practices of real-world deployments of agent-based technologies

Description: The innovative applications area aims to showcase successful applications and novel uses of agent-based technologies. We encourage research on emerging areas of agent-based applications with measurable benefits, on various topics such as (but not limited to) social good, sustainability, and ethical AI. The innovative applications area is keen to attract research that is not only triggered by real-world applications, but provides realistic beneficial solutions for these applications. Collaborations with relevant stakeholders is highly valued, as it helps demonstrate the feasibility and impact of the work.

Special Tracks

In addition to the main track, AAMAS 2025 will feature four special tracks: the AAAI Resubmissions Track, the Blue Sky Ideas Track, the JAAMAS Track, and the Demo Track, each with a separate Call for Papers (to be posted when available).

The focus of the Blue Sky Ideas Track is on visionary ideas, long-term challenges, new research opportunities, and controversial debate. The JAAMAS Track offers authors of papers recently published in the journal Autonomous Agents and Multiagent Systems (JAAMAS) that have not previously appeared as full papers in an archival conference the opportunity to present their work at AAMAS 2025. The Demo Track, finally, allows participants from both academia and industry to showcase their latest developments in agent-based and robotic systems.

Organizing Committee

AAMAS 2025 General Chairs:

Ann Nowé (Vrije Universiteit Brussel, Belgium)

Sanmay Das (George Mason University, USA)

AAMAS 2025 Program Chairs:

Amal El Fallah Seghrouchni (Sorbonne University, France)

Yevgeniy Vorobeychik (Washington University in Saint Louis, USA)

AAMAS 2025 Workflow Chairs:

Tao Zhang (Washington University in Saint Louis, USA)

Ayan Mukhopahdyay (Vanderbilt University, USA)

AAMAS 2025 Local Chair:

Michael Wellman (University of Michigan, Ann Arbor, USA)

If you have additional questions, please contact the program and workflow chairs using [email protected].