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

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: In a world where AI is increasingly prevalent and hybrid systems with humans and agents interacting becomes more frequent, it is crucial to study and create agents that can understand human social dynamics and have competent interaction with people. Significant challenges arise when transitioning from pure multiagent systems to hybrid systems that need to incorporate mixed-initiative from humans and agents, and sustain different competitive or collaborative social situations. Agents need new models and architectures to better address the interaction with people including, perception and recognition of human activities at different levels, interaction techniques that coordinate well with humans, and concerns for user experience and ethics, such as, trust and explainability. The design of human-agent interaction systems need special concerns that combine requirements from the perspectives of both the agents and the humans. The creation of agents with such capabilities can be inspired by human-human interactions and can, additionally, be applied to simulations with virtual humans or support the analysis of data from human social interactions.

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.