Call for Papers (Main Technical Track)

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: Reyhan Aydogan, 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].