Submission of abstracts (max 300 words) are conducted online utilizing EasyChair Conference Services. All authors should have an account with EasyChair so that your paper is associated to you, and you will receive decision notifications. Use an email address that is frequently monitored. All notifications, alerts and updates regarding your paper will be sent to this address. Create an account with EasyChair here.
Further information on paper submission and the required templates will be provided at a later date.
Abstract submission deadline: January 10, 2026
Abstract Acceptance Notice: January 20, 2026
Full paper deadline: March 1, 2026
Notification of acceptance: March 23, 2026
Conference dates: June 19–20, 2026
Accepted papers will be published in the CAS 2026 Proceedings (digital format). Selected papers may be invited for submission to a special journal issue or a follow-on edited volume.
Each paper must be presented by an author in person to be included in the proceedings.
We invite original research contributions that examine these principles and their role in shaping complex adaptive systems. We are particularly interested in work that addresses:
Adaptive learning and decision making: Individual and collective learning under dynamic and uncertain conditions, including social learning and distributed decision-making
Emergence and self-organization: Mechanisms in sociotechnical and engineering systems that give rise to global behavior from the interactions of its parts (micro-macro patterns of behavior) without centralized control
Agent-based simulation and modeling: Approaches beyond LLM-driven agent frameworks and traditional multi-agent systems, including hybrid modeling techniques
Sociotechnical Integration: Integration of adaptive systems within sociotechnical contexts including human, organizational, and societal structures
Methodological advances: Novel frameworks for that converge knowledge, analysis, modeling and simulation across spatial and temporal scales to support decision making, analysis of emergent phenomena and adaptive dynamics
Applications: Real world system domain studies that explore these principles such as autonomous systems, smart city infrastructure and disaster management.