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.