Proceedings of the Fourth International Workshop on Citizen-Centric Multiagent Systems 2026 (C-MAS 2026)

Abstract

Welcome to the fourth edition of C-MAS, the International Workshop on Citizen-Centric Multiagent Systems. C-MAS continues to explore how multiagent systems, autonomous agents, and AI-based sociotechnical systems can be designed around citizens as active participants rather than passive users, data sources, or service recipients. As AI systems increasingly mediate access to public services, information, mobility, finance, healthcare, and collective decision-making, it becomes essential to understand how citizens' preferences, values, rights, vulnerabilities, and strategic behaviours can be represented and respected.

C-MAS 2026 builds on the foundations established in previous editions by broadening the discussion around citizen agency, accountability, fairness, and participation. This year's accepted papers address a diverse set of topics, including accountability and explainability in citizen-centric MAS, emotionally intelligent human-AI interaction, biased social norms in large language models, long-term fairness dynamics, strategic behaviour in school choice and lending, multiagent reinforcement learning for cooperation and logistics, human-centric mobility services, algorithmic influence in information diffusion, and the realism of generative agents in social simulations.

The workshop also features a keynote by Dr. Roxana R\u{a}dulescu on human-aligned agents and multi-objective reinforcement learning. The keynote highlights a central challenge for citizen-centric AI, namely that many socially relevant problems involve multiple stakeholders, conflicting objectives, and trade-offs that cannot be reduced to a single reward signal. This perspective strongly resonates with the themes of C-MAS 2026, where the design of AI and multiagent systems requires not only technical performance or the optimisation of a single aspect, but also attention to transparency, trust, fairness, and human values.


We hope these proceedings provide a useful snapshot of current research on citizen-centric multiagent systems and help foster further collaboration across AI, multiagent systems, social simulation, responsible AI, public policy, and human-centred design. We thank all authors, reviewers, organisers, session chairs, and participants for contributing to the continuing development of the C-MAS community.

Further details about C-MAS 2026 are available on the workshop webpage: https://sites.google.com/view/cmas2026

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Identifiers

ORCID for Vahid Yazdanpanah: orcid.org/0000-0002-4468-6193

ORCID for Sebastian Stein: orcid.org/0000-0003-2858-8857

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