Original full papers
Up to 8 pages in length (excluding references) in ACM proceedings format; includes work accepted only as poster or extended abstract at AAMAS 2026.
Machine Learning/CORE Unranked
ALA 2026
The Eighteenth Workshop on Adaptive and Learning Agents
ALA 2026 is a workshop held in conjunction with AAMAS 2026 in Paphos, Cyprus, bringing together researchers to discuss advances in adaptive and learning agents across single- and multi-agent systems. It fosters collaboration among computer scientists and related fields by showcasing theoretical and practical work on learning, adaptation, coordination, and emergent behavior in dynamic and complex environments.
Key deadlines
Verified September 9, 2026Full paper
February 27, 2026
AoE
Workshop timeline
Submission and decisions
Full paperKey deadline
February 27, 2026 · AoE
Paper fit
Contribution paths
A strong submission should clearly identify its contribution and evaluate it appropriately.
Preliminary results / work-in-progress
Up to 6 pages in length; welcomes visionary outlook papers and early-stage research.
Journal paper abstracts
2-page abstracts of recently published journal papers.
Research areas in scope
01
Learning and Adaptation
Reinforcement learning (single- and multi-agent)Supervised and semi-supervised multi-agent learningRepresentation learning for single- and multi-agent systemsAdaptation in dynamic environmentsFoundation models for adaptive (multi-)agent systemsDeep learning approaches for adaptive single- and multi-agent systemsNovel combinations of reinforcement and supervised learning approachesIntegrated learning approaches using reasoning modules like negotiation, trust, coordination, etc.Batch and offline (multi-agent) reinforcement learningEvolutionary and open-ended learning in multi-agent populationsCo-evolution of agents in a multi-agent settingCooperative exploration and learning to cooperate and collaborateLearning trust and reputationHuman-in-the-loop learning systemsContinual reinforcement learningSelf-organizing, swarm, and bio-inspired adaptive multi-agent systemsNeuro-control in multi-agent systemsMulti-agent reinforcement learning and control for cyber-physical systems and robotics
02
Reasoning and Planning
Planning (single- and multi-agent)Reasoning (single- and multi-agent)Model-based RL and planning with learned world models (single- and multi-agent)Integrating learning with symbolic or game-theoretic reasoningNeurosymbolic and logical reasoning for (multi-agent) decision-makingNeuro-Symbolic Planning under Uncertainty in Unknown ModelsCausal Discovery via Adaptive Agents in Multi-Agent and Sequential Decision Tasks
03
Multi-Agent Systems and Coordination
Multi-objective optimisation in single- and multi-agent systemsGame theoretical analysis of adaptive multi-agent systemsDistributed learningDecentralized, federated, and communication-aware multi-agent learningCommunication restrictions and their impact on multi-agent coordinationDesign of reward structure and fitness measures for coordinationEmergent communication, information constraints, and their impact on multi-agent coordinationScaling learning techniques to large systems of learning and adaptive agentsEmergent behaviour in adaptive multi-agent systemsCoordination and communication among multiple agentsIncentive and mechanism designEmergence of collective behaviour in complex systems
04
Safety, Trust, and Ethics
Safety, robustness, and trustworthy (multi-agent) reinforcement learningLearning and modelling trust, reputation, and social norms in human–AI and multi-agent systemsSafe and Generalizable Reinforcement Learning via Logical Policy CompositionProvably Safe Policy Updates in Deep Reinforcement LearningDiscovering Agentic Safety Specifications from 1-Bit Danger SignalsEmbedded Safety-Aligned Intelligence for Multi-Agent Reinforcement LearningTrust-Aware Reinforcement Learning Agents in the Iterated Prisoners’ DilemmaDesigning ethical environments using multi-agent reinforcement learning
05
Applications and Real-World Systems
Applications of adaptive and learning agents and multi-agent systems to real world complex systemsHuman–AI interactionAutonomous Multi-Agent Penetration Testing with LLMs and Tool-Augmented ReasoningAdaptive Behavioral Alignment of RAG-Based Health Coaching AgentAdaptive Authentication Factor Selection in the Internet of ThingsAgential AI for Integrated Continual Learning, Deliberative Behavior, and Comprehensible Models
Policies worth checking twice
- All submissions are peer-reviewed under a double-blind process.
- Papers must be up to 8 pages (excluding references) in ACM proceedings format, following AAMAS formatting instructions.
- Submissions of preliminary results or visionary papers are limited to 6 pages.
- Journal paper submissions must be 2-page abstracts.
- Authors must remove AAMAS copyright block, citation information, and running headers; replace with specified \\setcopyright{none} and conference metadata.
- Camera-ready submissions must be deanonymized with the correct copyright block.
- Supplementary material (code, data, videos) may be included; appendices should be placed after references.
- Authors of submissions previously rejected or accepted as extended abstracts at AAMAS must append received reviews and a pdfdiff.
Official sources
Compiled from the official call for papers. The organizers’ pages remain authoritative.
Last verified September 9, 2026