Learning and Decision Making in Multi Agent Software Systems

Scope

The symposium welcomes contributions that study learning and decision processes in systems with multiple interacting agents. Themes include coordination and competition in software environments, learning dynamics in strategic settings, interest alignment and conflict resolution in distributed systems, reinforcement learning with interacting learners, and methods that support transparency and reliability in collective decision making. We also encourage work that connects theoretical progress with software applications in areas such as autonomous services, communication platforms, digital markets and distributed control. Submissions may be conceptual, methodological or application focused. Participants will have the opportunity to discuss new ideas, present ongoing work and engage with others who are developing techniques for complex interactive systems.