AAMAS 2027 Call for Papers (first call)

Call for Papers

The 26th International Conference on Autonomous Agents and Multiagent
Systems
Submission Instructions (Main Technical Track)Important Dates

   -

   Author registration on OpenReview: 17 Sep 2026
   -

   Abstract submission: 1 Oct 2026
   -

   Paper submission: 8 Oct 2026
   -

   Rebuttal period: 20 - 24 Nov 2026
   -

   Author notification: 21 Dec 2026
   -

   Camera-ready paper: 25 Jan 2027
   -

   Conference: 3 - 7 May 2027

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

For queries related to submission, please contact [email protected].

For responses to questions frequently asked by authors who wish to submit
to AAMAS, a FAQ page will be posted here soon.

Reciprocal reviewer policy: To ensure a fair distribution of reviewing load
and maintain high review quality, AAMAS has introduced a Reciprocal
Reviewer Policy [link
<https://warwick.ac.uk/fac/sci/dcs/aamas2027/calls/reciprocal-reviewer-policy/>
].
Areas of Interest

We welcome technical papers describing significant and original research on
all aspects of the theory and practice of autonomous agents and multiagent
systems, spanning established areas as well as emerging topics such as
generative and agentic AI. 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)
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   Generative and Agentic AI (GAAI)
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   Game Theory and Economic Paradigms (GTEP)
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   Coordination, Organizations, Institutions, Norms, and Ethics (COINE)
   -

   Search, Optimization, Planning, and Scheduling (SOPS)
   -

   Representation, and Reasoning (RR)
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   Engineering and Analysis of Multiagent Systems (EMAS)
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   Modelling and Simulation of Societies (SIM)
   -

   Human-Agent Interaction (HAI)
   -

   Robotics and Control (ROBOT)
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   Innovative Applications and Societal Impact (IASI)


Additionally, AAMAS 2027 includes several *special tracks*, as well as
submissions
from eligible non-archival workshops through its Workshop Outreach Pipeline;
details to follow.


Learning and Adaptation (LEARN)

Area Chairs: Stefano Albrecht, Ivana Dusparic, Akshat Kumar, Leandro
Marcolino, Stefano Mariani, Pradeep Varakantham, Yaodong Yang, Chongjie
Zhang

Topics:

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   Reasoning and learning under uncertainty
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   Supervised learning
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   Unsupervised and representation learning
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   Reinforcement learning
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   Multiagent learning
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   Evolutionary and biologically inspired algorithms
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   Learning agent capabilities
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   Learning agent-to-agent interactions, including learning to communicate
   and emergent communication
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   Human-in-the-loop learning
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   Few-shot learning
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   Distributionally robust learning
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   Adversarial learning
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   Imitation learning

Description:

This area welcomes papers whose primary contribution concerns learning and
adaptation in single-agent or multiagent systems. Relevant submissions
include theoretical, algorithmic, and empirical work on supervised,
unsupervised, reinforcement, imitation, evolutionary, adversarial, robust,
and human-in-the-loop learning, as well as learning agent capabilities and
agent-to-agent interactions.

Papers should be submitted to LEARN when the main contribution is a
learning method, learning-theoretic analysis, or empirical study of
learning in agent or multiagent settings. Papers focused primarily on
generative-model-based agent architectures, workflows, or evaluation should
be submitted to GAAI.

Generative and Agentic AI (GAAI)

Area Chairs: Bo An, Giovanni Ciatto, Amit Chopra, Yali Du, Andrei Olaru,
Eugene Vorobeychik, Weinan Zhang

Topics:

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   Memory, state, context, long-lived interaction, and other architectural
   patterns for generative and agentic AI systems
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   Orchestration and workflows of agents and tools
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   Runtime support, infrastructure, and engineering for generative and
   agentic AI systems
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   Embodied, multimodal, and grounded generative AI agents
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   Open-ended, autonomous, and self-improving agents based on generative AI
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   Planning, reasoning, and long-horizon agentic workflows
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   Agency and learning in generative and agentic AI
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   Interaction protocols for agentic AI
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   Coordination, cooperation, and negotiation in generative AI agents
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   Normative reasoning and institutional constraints for generative AI
   agents
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   Theory of mind, user modeling, and social reasoning in generative AI
   agents
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   Hybrid classic-generative agents, with a focus on how generative AI
   agents use classical tools, models, and protocols
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   Failure handling, recovery, and resilience in agentic AI
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   Modeling and analysis of generative AI agents
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   Instruction following and multi-turn agent behavior in generative AI
   agents
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   Human-agent interaction for delegation, feedback, and task collaboration
   in generative AI agents
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   Agentic decision support and decision boundaries
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   Alignment, learning from human feedback, and controllability of
   generative and agentic AI systems
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   Explainability, introspection, and debugging for generative AI agents
   and systems
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   Assurance, verification, and safety in generative and agentic AI systems
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   Benchmarks, evaluation, and metrics for generative and agentic AI systems
   -

   Generative AI-supported specification and implementation of agents and
   multiagent systems
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   Agentic AI applications in science, software, education, and critical
   domains

Description:

This area welcomes papers whose primary contribution advances generative
and agentic AI systems, namely agents or multiagent systems that act,
reason, interact, coordinate, or make decisions by using, integrating, or
analyzing generative AI models. Relevant submissions may address
foundations, architectures, learning methods, orchestration, tool use,
evaluation, safety, alignment, verification, governance, deployment, and
human-agent or multiagent interaction in generative-agent systems.

Papers should be submitted to GAAI when the central technical contribution
concerns agents whose capabilities, architecture, reasoning, interaction,
learning, evaluation, or deployment substantially rely on generative AI
models. Papers whose main contribution is a general learning, planning,
engineering, governance, or human-interaction method should instead be
submitted to the corresponding AAMAS area, unless the generative-agent
aspect is central.

Submissions where the core contribution is not specifically about agents or
multiagent systems are out of scope. Advances in language models, prompt
engineering, generic tool use, or arbitrary generative tasks are outside
the scope of this area unless they make a clear contribution to autonomous
agents or multiagent systems.

Game Theory and Economic Paradigms (GTEP)

Area Chairs: Haris Aziz, Branislav Bosansky, Vincent Conitzer, Christopher
Kiekintveld, Villiam Lisy, Pinyan Lu, Thanh Nguyen, Haifeng Xu, Dengji Zhao

Topics:

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   Auctions and mechanism design
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   Economic foundations and market design for economics of AI agents
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   Bargaining and negotiation
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   Behavioural game theory
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   Evolutionary game theory
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   Non-cooperative games: equilibrium concepts
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   Non-cooperative games: computational issues
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   Non-cooperative games: theory and applications
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   Voting and preference aggregation
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   Social choice and social networks
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   Judgment aggregation and forecasting
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   Fair allocation and matching
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   Tournaments and agent evaluation
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   Digital and liquid democracy
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   Strategic coalition formation
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   Cooperative games
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   Persuasion and information design


Description:

This area welcomes papers whose primary contribution advances game theory,
economic paradigms, mechanism design, market design, social choice, or
strategic decision-making for agents and multiagent systems. Relevant
submissions include theoretical, computational, and applied work on
cooperative and non-cooperative games, equilibrium computation, auctions,
bargaining, negotiation, voting, allocation, matching, persuasion,
information design, and economic models of AI agents.

Papers should be submitted to GTEP when the strategic, economic,
game-theoretic, or social-choice model is central to the contribution.
Papers focused mainly on norms, institutions, ethics, or organizational
governance should be submitted to COINE unless the strategic or economic
model is central.

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

Area Chairs: Pradeep K. Murukannaiah, Vahid Yazdanpanah

Topics:

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   Coordination and teamwork
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   Social network analysis
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   Norms and normative systems
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   Multiagent organizations and institutions
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   Non-strategic coalition or team formation
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   Communication, including communication using natural language
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   Policy, regulation, and accountability
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   Safety, robustness, trust, and reputation
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   Ethical considerations, including bias, equity, fairness, privacy,
   safety, security, and transparency
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   Values and preferences
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   Agreement technologies: negotiation and argumentation
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   Responsible socio-technical systems
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   Explainability and interpretability of norms and ethics in human-agent
   teams
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   Ethical and governance challenges of LLM-based agents in coordination,
   organizations, institutions, and normative systems
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   Rebellion and disobedience in AI

Description:

This area welcomes papers whose primary contribution concerns coordination,
organizations, institutions, norms, ethics, accountability, governance, and
responsible behavior in agent and multiagent systems. Relevant submissions
include theoretical, computational, empirical, and design-oriented work on
teamwork, social reasoning, normative systems, institutions, trust,
reputation, values, policy, regulation, agreement technologies, and
responsible socio-technical systems.

Research in agent and multiagent systems has a long history of balancing
agent autonomy, adaptation, and distributed social reasoning with
system-level considerations such as organizational and institutional policy
enforcement, safety, security, fairness, and accountability. Submissions
may address machine-machine cooperation, human-machine cooperation, and
multiagent coordination, especially where these raise questions of
transparency, trust, responsibility, governance, or alignment with social
norms and ethical values.

Papers should be submitted to COINE when social, institutional, normative,
organizational, governance, or ethical dimensions are central to the
contribution. Papers focused primarily on human-subject interaction design
or evaluation should be submitted to HAI; papers focused primarily on
generative-agent architectures should be submitted to GAAI.

Search, Optimization, Planning, and Scheduling (SOPS)

Area Chairs: Prashant Doshi, Sarah Keren, Stefania Monica, Felipe
Meneguzzi, Roni Stern, Nathan Sturtevant

Topics:

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   Single-agent planning and scheduling
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   Multiagent planning and scheduling
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   Decentralized planning and scheduling
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   Planning under uncertainty
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   Decision-theoretic planning
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   Temporal reasoning and scheduling
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   Combinatorial optimization
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   Constraint programming
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   Distributed constraint reasoning
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   Resource and task allocation
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   Non-strategic coalition formation
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   Plan and goal recognition
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   Human-aware planning and scheduling
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   Knowledge representation methods for search, optimization, planning, and
   scheduling


Description:

This area welcomes theoretical and experimental contributions to search,
optimization, planning, and scheduling in single-agent and multiagent
systems. Relevant submissions include decentralized planning, planning
under uncertainty, decision-theoretic planning, temporal reasoning and
scheduling, combinatorial optimization, constraint programming, distributed
constraint reasoning, resource and task allocation, plan and goal
recognition, human-aware planning and scheduling, and non-strategic
coalition formation.

Contributions that integrate learning-based methods, including foundation
models, with search, optimization, planning, and scheduling techniques are
welcome, provided that the primary contribution remains in the SOPS area.
Similarly, approaches to motion and path planning are relevant when they
are framed as planning, search, or decision-making problems for autonomous
agents or multiagent systems.

Papers should be submitted to SOPS when the primary contribution is a
search, optimization, planning, scheduling, or decision-theoretic method,
even if the method is applied to multiagent, robotic, human-aware, or
foundation-model-assisted settings.

Representation and Reasoning (RR)

Area Chairs: Yves Lesperance, Ken Satoh, Tran Cao Son

Topics:

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   Neurosymbolic approaches
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   Argumentation
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   Agent theories and models
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   Explainability
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   Logics for agent reasoning
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   Ontologies for agents
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   Reasoning about knowledge, beliefs, goals, actions, plans, and change in
   multiagent systems
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   Reasoning and problem solving in agent-based systems
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   Verification of agents and multiagent systems
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   Autoformalization
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   Logic-constrained learning
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   Strategic reasoning and strategy logics

Description:

This area welcomes theoretical and experimental contributions to knowledge
representation and reasoning for single-agent and multiagent systems.
Relevant submissions include formal and computational approaches to agent
theories, logics for agent reasoning, argumentation, ontologies, knowledge
graphs, semantic frameworks, strategic reasoning, reasoning about
knowledge, beliefs, goals, actions, plans, and change, verification,
autoformalization, logic-constrained learning, and neurosymbolic reasoning.

Knowledge representation is interpreted broadly, encompassing formal
approaches such as epistemic, strategic, and description logics, as well as
data-driven techniques such as representation learning, when they support
reasoning in agent or multiagent systems. Relevant reasoning paradigms
include automated reasoning, theorem proving, verification-based
approaches, probabilistic inference, neurosymbolic methods, and reasoning
methods that support trustworthiness, accountability, transparency,
fairness, explainability, or responsible AI.

Papers should be submitted to RR when the primary contribution is a
representation or reasoning framework, method, analysis, or formalism for
agents or multiagent systems. Papers whose primary contribution is
planning, scheduling, or optimization should be submitted to SOPS, unless
the representation or reasoning formalism is central.

Engineering and Analysis of Multiagent Systems (EMAS)

Area Chairs: Rem Collier, Roberto Micalizio, Sebastian Rodriguez

Topics:

   -

   Requirements capture and formal specification of multiagent systems
   -

   Programming paradigms and languages for autonomous agents
   -

   Runtime infrastructures and deployment platforms for scalable MAS,
   including cloud, edge, and hybrid settings
   -

   Testing, debugging, verification, validation, certification, and DevOps
   for multiagent systems
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   Scalability, fault tolerance, and performance engineering of MAS
   platforms
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   Engineering self-adaptive agents, including lifecycle management,
   continuous evolution, and deployment pipelines
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   Interoperability, business agreements, and agent-to-agent protocols
   -

   Declarative, logic-based, and BDI agent programming and architectures
   -

   Engineering MAS-based simulations for rigorous analysis and
   experimentation
   -

   Sociotechnical governance tools for norms, ethics, and accountability
   -

   Human-centered engineering for usability, transparency, and
   explainability
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   Open-source toolchains, benchmarks, and reproducible MAS testbeds
   -

   Engineering learning agents, including platform design and online
   adaptation
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   Engineering MAS with LLM methods
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   Hybrid symbolic-subsymbolic agent systems, including engineering
   architectures and platforms for neurosymbolic reasoning
   -

   Benchmarks, evaluation methodologies, and reproducible workflows for MAS
   -

   Data-driven engineering processes for design, testing, and adaptation of
   agent systems
   -

   Engineering MAS-based autonomous systems

Description:

This area welcomes papers whose primary contribution advances the
engineering and analysis of agents and multiagent systems. Relevant
submissions include work on software abstractions, programming languages,
methodologies, architectures, runtime infrastructures, deployment
platforms, testing, debugging, verification, validation, certification,
monitoring, interoperability, scalability, reproducibility, and lifecycle
management.

Papers integrating symbolic reasoning, learning, LLM-based components, or
neurosymbolic methods are welcome when the focus is on engineering
challenges and solutions. The area also welcomes contributions on
engineering agent and multiagent systems whose behaviour, decisions,
interactions, and failures are understandable to human users. This includes
methods and tools for designing transparency into agent architectures,
tracing and auditing agent behaviour, generating explanations of individual
or collective decisions, monitoring compliance with requirements and norms,
and supporting accountability in deployed systems.

Papers should be submitted to EMAS when the primary contribution concerns
methods, tools, languages, platforms, infrastructures, or processes for
engineering, deploying, testing, validating, maintaining, or analyzing
agent and multiagent systems. Papers in which LLMs or other AI technologies
perform the primary task while MAS engineering plays only a background role
should be submitted to another area.

Modeling and Simulation of Artificial Societies (SIM)

Area Chairs: Paul Davidsson, Önder Gürcan, Takayuki Ito

Topics:

   -

   Modeling for agent-based simulation
   -

   Simulation of complex systems
   -

   Modeling of societies and social simulations
   -

   Agent-based modeling and evaluation of public policies
   -

   Simulation techniques, tools, and platforms
   -

   Analysis of agent-based simulations
   -

   Calibration, verification, and validation of agent-based simulation
   systems
   -

   Robustness, reliability, and trustworthiness of agent-based simulations
   -

   Design and implementation of large-scale agent-based simulations
   -

   High-performance computing and frameworks for agent-based simulation
   -

   Interactive and participatory simulation
   -

   LLM-supported agent-based simulation and modeling

Description:

This area welcomes papers whose primary contribution concerns agent-based
modeling and simulation of artificial societies and complex systems.
Relevant submissions include modeling methods, simulation techniques, tools
and platforms, calibration, verification, validation, robustness,
participatory simulation, large-scale simulation, and the analysis of
emergent behavior in social, organizational, economic, ecological,
transportation, and socio-technical systems.

Artificial societies are computer simulations or models created to emulate
and study the behavior of complex social systems. Agent-based models
provide a way to analyze how individual behaviors, interactions,
incentives, policies, and interventions give rise to emergent structures
and dynamics at the system level. Relevant application areas include
ecology, biology, economics, transportation, management, organizational
studies, and the social sciences.

Papers should be submitted to SIM when simulation is central to the
contribution, either as a methodological advance or as a way to explain,
predict, explore, or evaluate complex systems.

Human-Agent Interaction (HAI)

Area Chairs: Reuth Mirsky, Sarath Sreedharan

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
   -

   Agent models and architectures for interaction with humans
   -

   Design for human-agent interaction
   -

   Virtual humans
   -

   Theory of mind and user modeling in human-agent interaction
   -

   Modelling, detecting, and accounting for deception in human-AI teams
   -

   Human cognitive modeling for agent interaction

Description:

This area welcomes papers whose primary contribution concerns the design,
modeling, evaluation, or analysis of interaction between humans and agents.
Relevant submissions include work on human-agent interaction, socially
interactive agents, human-robot interaction, mixed-initiative and shared
autonomy, groups of humans and agents, trust, explainability, deception,
theory of mind, cognitive modeling, virtual humans, and agent architectures
for interaction with humans.

Human interaction with artificially intelligent agents is becoming
increasingly common in the social and organizational contexts through which
people make decisions, coordinate work, and act in the world. Significant
challenges arise when moving from purely multiagent systems to hybrid
systems that incorporate bidirectional human-agent interaction in
competitive, cooperative, or mixed settings. Agents need models and
architectures that support perception and recognition of human states and
activities, interaction modalities that enable coordination, and careful
consideration of human factors and ethical concerns.

Papers should be submitted to HAI when human-agent interaction is central
to the research question, methodology, or evaluation. Papers focused
primarily on institutional, normative, or governance aspects should be
submitted to COINE; papers focused primarily on generative-agent
architectures should be submitted to GAAI.

Robotics and Control (ROBOT)

Area Chairs: Chris Amato, Sven Koenig, Peter Stone

Topics:

   -

   Coordination and collaboration in robotic systems
   -

   Swarm and multi-robot collective behavior
   -

   Robots in adversarial settings
   -

   Perception and vision for autonomous robots
   -

   Networked systems and distributed robotics
   -

   Foundation models for autonomous robots and robot teams
   -

   Knowledge representation and reasoning in robotic systems
   -

   Robot planning and decision-making
   -

   Mapping, localization, and navigation for autonomous robots and robot
   teams
   -

   Autonomous robot manipulation and task execution
   -

   Decision-making and control for autonomous robots and robot teams
   -

   Robot learning for autonomy and adaptation
   -

   Long-term or lifelong autonomy for robotic systems
   -

   Execution monitoring and failure recovery for robots
   -

   Robot modeling and simulation for autonomous agents
   -

   Explainability, trust, and ethics for robots
   -

   Hybrid systems of robots with humans and/or software agents

Description:

This area welcomes papers whose primary contribution concerns autonomous
robots, robotic agents, multi-robot systems, or the interaction of robots
with humans, software agents, or physical environments. Relevant
submissions include work on coordination, collaboration, swarms,
distributed robotics, robot planning, robot learning, knowledge
representation and reasoning for robots, long-term autonomy, execution
monitoring, failure recovery, modeling and simulation, explainability,
trust, ethics, decision-making, and control for autonomous robots.

Robots are embodied and situated agents that operate in the physical world.
Research on autonomous agents and multiagent systems shares many challenges
and synergies with intelligent robotics, especially where robotic systems
must reason, learn, plan, coordinate, adapt, or act autonomously in
realistic settings.

Submissions involving perception, vision, mapping, localization,
manipulation, or control are welcome when these components are integrated
into, or make a clear contribution to, autonomous robots or multi-robot
systems.

Innovative Applications and Societal Impact (IASI)

Area Chairs: Georgina Curto, Stéphane Galland, Alessandro Ricci

Topics:

   -

   Deployed or emerging applications of agent-based and agentic systems
   addressing real-world challenges
   -

   Agent-based and agentic systems for social good, sustainability, public
   policy, education, health, science, industry, and critical domains
   -

   Realistic agent-based and agentic models of human organizations,
   institutions, and socio-technical systems
   -

   Evaluation of the cognitive, social, organizational, or decision-support
   capabilities of agent-based and agentic systems in real-world settings
   -

   Integration of agent-based and agentic systems with other AI, software,
   cyber-physical, robotic, simulation, or decision-support technologies
   -

   Hybrid agent-based, agentic AI, and reinforcement learning solutions for
   real-world applications
   -

   Deployment, adoption, usability, robustness, safety, and maintainability
   of agent-based and agentic technologies in practice
   -

   Challenges, best practices, and lessons learned from real-world
   deployments of agent-based and agentic technologies
   -

   Evaluation methodologies, benchmarks, and evidence of measurable impact
   for innovative applications
   -

   Stakeholder involvement, participatory design, and co-creation of
   agent-based and agentic applications
   -

   Ethical, legal, societal, and environmental implications of deployed or
   emerging agent-based and agentic systems
   -

   Frameworks, platforms, and tools supporting the implementation and
   deployment of innovative agent-based and agentic applications

Description:
This area welcomes papers whose primary contribution is an innovative
application or demonstrated societal impact of agent technologies. Relevant
submissions include deployed systems, emerging applications, realistic
prototypes, stakeholder-driven designs, and rigorous evaluations of
autonomous agents and multiagent systems addressing real-world challenges.

Submissions should clearly explain the application context, the role of
agents, the novelty of the application, and the evidence of benefit,
feasibility, adoption, or measurable impact. Collaborations with relevant
stakeholders are strongly encouraged, especially where they demonstrate
that the proposed approach addresses a real need and can be used,
evaluated, or deployed in practice.

Papers should be submitted to IASI when the primary contribution is an
innovative application, deployment, realistic validation,
stakeholder-driven design, or demonstrated societal impact of agent-based
or agentic technologies. Papers whose primary contribution is a new
algorithm, architecture, learning method, engineering tool, or simulation
method should be submitted to the corresponding technical area unless the
application or impact contribution is central.

For submission instructions, see [LINK
<https://warwick.ac.uk/fac/sci/dcs/aamas2027/calls/instructions/>]

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. Papers
may be moved to a different area based on fit but may be desk rejected if
deemed out of scope.

Papers submitted to AAMAS 2027 could be selected for publication in the
Proceedings of AAMAS 2027 under a CC-BY licence. Papers that are not
selected will be automatically considered for publication in the Findings
of AAMAS 2027 under a CC-BY licence, unless the authors opt out of this
option in the submission form (see more information about AAMAS 2027
Findings here [LINK
<https://warwick.ac.uk/fac/sci/dcs/aamas2027/calls/findings/>]). Papers
selected for publication in the Proceedings and papers selected for
publication in the Findings have the same length and follow the same
submission format. Papers that are not selected for either will be
rejected.

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