WorkshopsACSOS 2026

Accepted Workshops

The 7th IEEE International Conference on Autonomic Computing and Self-Organizing Systems (ACSOS 2026) will be accompanied by the following workshops:

• 13th Workshop on Self-Improving Systems Integration (SISSY)
• 4th International Workshop on Sustainable and Scalable Self-Organisation (SaSSO-4)
• 4th International Workshop on Artificial Intelligence for Autonomous computing Systems (AI4AS)
• 1st International Workshop on AI-Driven Cyber-Resilience for Autonomous Cyber-Physical Systems (AICR-ACS)

13th Workshop on Self-Improving Systems Integration (SISSY)

Information and communication technology (ICT) pervades every aspect of our daily lives. This changes our communities and all of our human interactions. It also presents a significant set of challenges in correctly designing and integrating our resulting technical systems. For instance, the embedding of ICT functionality in more and more devices (such as household appliances or thermostats) leads to novel interconnections and a changing structure of the overall system.

Not only are technical systems increasingly coupled, but also numerous previously isolated natural and human systems have merged into a kind of overall system-of-systems – an interwoven system structure.

This change of structure is fundamental and affects the whole production cycle of technical systems; standard system integration and testing is not feasible any more. The increasingly complex challenges of developing the right type of modelling, analysis, and infrastructure for designing and maintaining ICT infrastructures has continued to motivate the self-organising, autonomic and organic computing systems community.

Integration is more than just putting things together. Consequently, this workshop intends to study novel approaches to system-of-systems integration, maintenance and testing by applying self-* principles. Specifically, we seek approaches that allow for a continual process of self-integration among components and systems that are self-improving and evolving over time towards an optimised and stable solution.

The workshop intends to focus on the important work of applying self‐* principles to the integration of "Interwoven Systems" (where an "Interwoven System" is a system cutting across several technical domains, combining traditionally engineered systems, systems making use of self‐* properties and methods, and human systems).

The goal of the workshop is to identify key challenges involved in creating self‐integrating systems and consider methods to achieve continuous self‐improvement for this integration process. The workshop specifically targets an interdisciplinary community of researchers (i.e. from systems engineering, complex adaptive systems, socio‐technical systems, and the OC/AC domains) in the hope that collective expertise from a range of domains can be leveraged to drive forward research in this area.

Workshop organizers:
Kirstie Bellman
Ada Diaconescu
Lukas Esterle
Sven Tomforde

More information can be found on the workshop’s website: https://sissy-workshop.github.io/

4th International Workshop on Sustainable and Scalable Self-Organisation (SaSSO-4)

The fourth SaSSO workshop explores inter-organizational self-organization to address sustainability and scalability challenges. Domains like healthcare, transportation, and food systems are all examples of complex, interdependent systems requiring multi-stakeholder coordination.

This highlights a pressing need to re-consider, integrate and re-vitalise concepts of self-organisation, self-governance, sustainability, and multi-scale systems thinking in order to meet the challenges involved in shaping real-world complex systems.

The goal of this inter-disciplinary workshop is to address two contrasting pairs of inter-related research questions:

• Sustainability of self-organisation: considering path dependency, the iron law of oligarchy, and the avoidance of tyranny, as well as self-organisation for sustainability inspired by Ostrom’s work and cooperative survival dilemmas.
• Scalability of self-organisation: addressing how decision-making, dispute resolution, and monitoring evolve with system size, and how self-organised rules adapt over time (concept drift).

SaSSO welcomes both applied and theoretical contributions addressing these challenges.

Workshop organizers:
Simon T. Powers
Stefan Sarkadi
Tobias Buhl

More information can be found on the workshop’s website: https://cosocials.org/sasso-2026

4th International Workshop on Artificial Intelligence for Autonomous computing Systems (AI4AS)

Modern computing systems are increasingly heterogeneous and operate at unprecedented scale across the cloud–edge continuum. Their structural and operational complexity often exceeds what can be effectively managed through manual configuration or static control logic.

The rapid evolution of Artificial Intelligence (AI) and Machine Learning (ML) techniques – including generative AI, agentic AI, edge intelligence, as well as collaborative and federated learning – has opened new avenues for engineering more robust, sustainable, and secure computing infrastructures.

However, there are still several challenges to face regarding the applicability of AI and ML techniques across diverse domains, especially in terms of accuracy, robustness, explainability, safety, security, performance, and sustainability.

In this workshop, we solicit high-quality contributions that fit with the overarching theme of AI and ML meeting autonomous computing systems.

Topics include:

• AI and ML techniques for self-* computing systems
• Architectures and frameworks for AI integration
• Sustainability aspects of AI-driven adaptation
• AI ethics, bias mitigation, and trustworthiness in self-adaptive systems
• Collaborative, federated, continual and multi-agent learning approaches
• Robustness, explainability, safety, and security
• Agentic AI in autonomous systems
• Edge intelligence and distributed decision-making
• Self-adaptation for AI/ML systems
• Case studies and real-world implementations

Workshop organizers:
Valeria Cardellini
Davide Domini
Lukas Esterle
Stefano Iannucci
Gabriele Russo Russo

More information can be found on the workshop’s website: https://ai4as.github.io/

1st International Workshop on AI-Driven Cyber-Resilience for Autonomous Cyber-Physical Systems (AICR-ACS)

Autonomous cyber-physical systems (CPS) increasingly operate in adversarial and highly dynamic environments, including industrial control systems, smart energy infrastructures, transportation systems, and distributed edge-cloud platforms. As these systems integrate AI components and autonomic control mechanisms, cybersecurity must evolve from static protection toward runtime autonomous defense.

Unlike traditional cybersecurity research, which often focuses on detection algorithms or cryptographic protocols in isolation, AICR-ACS emphasizes security as an autonomic capability: the integration of threat detection, decision-making, and mitigation within self-adaptive control loops (e.g., MAPE-K).

The goal is to design systems capable of continuously monitoring their security posture, reasoning about threats, and autonomously adapting their configuration or behavior to maintain operational guarantees.

Topics of Interest (non-exhaustive)

• AI/ML-based intrusion detection in CPS and OT environments
• Online and continual learning for adaptive threat detection
• Reinforcement learning for automated mitigation
• Security-aware MAPE-K loops and autonomic control
• Multi-agent coordination for distributed cyber-defense
• Adversarial robustness of AI-based security systems
• Explainable AI for security-critical CPS
• Self-adaptive cryptographic frameworks
• Post-quantum cryptography migration strategies
• Cryptographic agility in long-lived infrastructures
• Cybersecurity digital twins
• Security of smart grids, industrial IoT, autonomous mobility systems
• Experimental testbeds, cyber ranges, and reproducibility studies

Workshop organizers:
Stefano Iannucci
Riccardo Torlone
Massimo Celino

More information can be found on the workshop’s website: https://aicr-acs.github.io/

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