TY - GEN
T1 - Macro-Types in Multi-Scale Feedback Systems
T2 - 6th IEEE International Conference on Autonomic Computing and Self-Organizing Systems, ACSOS 2025
AU - Diaconescu, Ada
AU - Di Felice, Louisa Jane
AU - Mellodge, Patricia
AU - Zahadat, Payam
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025/1/1
Y1 - 2025/1/1
N2 - Large Complex Adaptive Systems (CAS) operate at multiple scales-processing various information flows, encoded at different granularities, over different substrates. Often, system scales are interconnected by feedback cycles, with micro-scales generating macro-scales, in turn influencing the micro-scales, and so on. E.g. foraging ants (micro) contribute to a pheromone trail (macro), which in turn guides their movement (micro) and updates the trail (macro). As these processes take widely different forms when occurring in different environments and accomplishing different functions, they may be difficult to detect, compare and transfer across CAS domains. We previously generalised such diverse processes, defining them explicitly as a Multi-Scale Feedback Systems (MSFS) design pattern. In this paper, we propose a conceptual framework for categorising macroprocesses in MSFS. This helps identify and analyse micro-macro feedback cycles across CAS domains; and engineer new CAS with specific constraints. We illustrate these concepts via CAS examples that fit the MSFS pattern via different variants. This contribution extends the theoretical basis of MSFS for dealing with the increasing complexity of modern environments.
AB - Large Complex Adaptive Systems (CAS) operate at multiple scales-processing various information flows, encoded at different granularities, over different substrates. Often, system scales are interconnected by feedback cycles, with micro-scales generating macro-scales, in turn influencing the micro-scales, and so on. E.g. foraging ants (micro) contribute to a pheromone trail (macro), which in turn guides their movement (micro) and updates the trail (macro). As these processes take widely different forms when occurring in different environments and accomplishing different functions, they may be difficult to detect, compare and transfer across CAS domains. We previously generalised such diverse processes, defining them explicitly as a Multi-Scale Feedback Systems (MSFS) design pattern. In this paper, we propose a conceptual framework for categorising macroprocesses in MSFS. This helps identify and analyse micro-macro feedback cycles across CAS domains; and engineer new CAS with specific constraints. We illustrate these concepts via CAS examples that fit the MSFS pattern via different variants. This contribution extends the theoretical basis of MSFS for dealing with the increasing complexity of modern environments.
KW - complex adaptive systems
KW - deployment types design pattern
KW - feedback
KW - framework
KW - Macro
KW - micro
KW - multi-scale
UR - https://www.scopus.com/pages/publications/105025043105
U2 - 10.1109/ACSOS66086.2025.00023
DO - 10.1109/ACSOS66086.2025.00023
M3 - Conference contribution
AN - SCOPUS:105025043105
T3 - Proceedings - 2025 IEEE International Conference on Autonomic Computing and Self-Organizing Systems, ACSOS 2025
SP - 64
EP - 75
BT - Proceedings - 2025 IEEE International Conference on Autonomic Computing and Self-Organizing Systems, ACSOS 2025
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 29 September 2025 through 3 October 2025
ER -