The IEEE International Conference on Autonomic Computing and Self-Organizing Systems (ACSOS) is a premier venue for advancing research in autonomic computing, self-adaptation, and self-organization. Established in 2020 through the merger of two influential IEEE conferences—ICAC (International Conference on Autonomic Computing) and SASO (International Conference on Self-Adaptation and Self-Organization)—ACSOS builds on more than two decades of excellence in these fields. The conference serves as a hub for interdisciplinary collaboration, bridging academic and industrial perspectives across domains such as artificial intelligence, computational biology, and computer systems. ACSOS features a diverse program, including research papers, experience reports, posters, demonstrations, and a doctoral symposium, fostering innovation and knowledge exchange.

ACSOS 2025 invites submissions on theoretical aspects, modeling, design, implementation, evaluation, verification and practical applications of autonomic, self-adaptive, self-organizing, and multi-agent systems, algorithms and techniques. This includes, but is not limited to:

Models and Algorithms: bio-inspired and socially inspired paradigms and heuristics; collective behavior of decentralized agents and systems; swarm intelligence; evolution and learning; organic computing; requirement and goal expression techniques; formal expressions of uncertainty; agent based modeling to help understand existing systems; digital twins

Theoretical aspects: theoretical frameworks; formal languages; game theory; queuing and control theory; symbolic knowledge representation

Systems properties: performance; robustness; resilience/dependability/reliability; trustworthiness; resource and energy efficiency; stability; diversity; self-protection and cybersecurity; self-reference and reflection; emergent behavior; explainability; interpretability; computational awareness and self-awareness

Engineering aspects: design patterns; programming languages; architectures; operating systems and middleware; testing, validation, and assurance methodologies; runtime models; large-scale, decentralized and multi-agent systems; data science and analytics; machine learning and artificial intelligence; communication and intelligent routing; distributed learning including federated learning; multi agent infrastructures

Cross disciplinary methods: approaches that draw inspiration from complex systems, chemistry, psychology, sociology, biology, and ethology

Socio-technical factors: human and social factors; visualization; crowdsourcing and collective awareness; guardrails and legal/regulatory compliance in self-* techniques; trust, ethics, privacy, sustainability, social and environmental implications.

Applications: We welcome papers in all application domains – past editions have featured papers on, for example, applications of multi-agent systems in various areas, enterprise applications, cyber-physical systems, smart agriculture, federated LLMs, manufacturing, autonomous vehicles, or smart (virtual) environments, disaster response, “smart” traffic management, datacenter infrastructure, resource management and scheduling, “smart” grids, automation in scientific computing and scientific discovery, virtual reality, and human-machine interfacing.