Challenge and Scope

The world is increasingly embracing autonomous systems: in robotics, manufacturing, software engineering, vehicles, data center systems, and precision agriculture to name just a few areas. These systems are bringing autonomy to a whole new level of dynamic decision-making under uncertainty, requiring autonomic behavior (e.g., control theory, cybernetics) and self-reference, leading to a range of self-* properties (e.g., self-awareness, self-adaptation, self-organization), and an approach in which system implementation and its environment are holistically considered.

Despite this rise in autonomic and self-* systems, there remains a wide range of fundamental challenges in understanding how to design, control, reason about, and trust such systems. The IEEE ACSOS conference solicits novel research on these topics, in fundamentals and methods as well as applications for autonomic and self-* systems. ACSOS is particularly proud of its long-standing academic breadth and innovative industry contributions, and regularly features work from computational biologists through to operating systems researchers – united by the common theme of autonomous systems. The conference program will include research papers, in-practice experience reports, posters, demos, and a doctoral symposium. ACSOS 2023 solicits contributions from among (but not limited to) the following autonomic and self-adaptive and self-organizing methods and applications:

Fundamentals and Methods

    Systems theory: bio-inspired and socially-inspired paradigms and heuristics; evolution and learning; self-aware computing; organic computing; theoretical frameworks; formal languages; queuing and control theory; requirement and goal expression techniques; uncertainty as a 1st class entity
    System properties: performance; robustness; resilience; dependability and reliability; trustworthiness; resource and energy efficiency; stability; anti-fragility; diversity; self-protection and cybersecurity; self-reference and reflection; emergent behavior; computational awareness and self-awareness
    Systems and software engineering: algorithms; 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
    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; trust, ethics, privacy, social and environmental implications.

Applications

Applications of the autonomic, self-adaptive and self-organizing methods in practice, including but not limited to:

    Hardware and software systems, including operating systems, storage, and networking, across areas such as Internet of Things, cloud, fog and edge computing, and high-performance computing
    Next-generation industry, including cyber-physical systems, smart agriculture, manufacturing, autonomous vehicles, or smart (virtual) environments
    Social and hybrid systems, such as crowd or traffic modeling, political or social structures, game theory, virtual reality, interactive systems, and human-machine interfacing.