Self-adaptive systems (SASs) are increasingly leveraging autonomy in their decision-
making to manage uncertainty in their operating environments. A key problem with SASs is …

Approaches that support the decision-making of self-adaptive and autonomous systems
(SAS) often consider an idealized situation where (i) the system's state is treated as fully …

[Context/Motivation] A model at runtime can be defined as an abstract representation of a
system, including its structure and behaviour, which exist alongside with the running system …

Models are not static entities: they evolve over time due to changes. Changes may
inadvertently and surprisingly violate constraints imposed. Therefore, the models need to be …

Decision-making for self-adaptation approaches need to address different challenges,
including the quantification of the uncertainty of events that cannot be foreseen in advance …

In Autonomous and Intelligent systems (AIS), the decision-making process can be divided
into two parts:(i) the priorities of the requirements are determined at design-time;(ii) design …

Self-adaptive systems (SAS) need to reflect on the current environment conditions, their past
and current behaviour to support decision making. Decisions may have different effects …

Runtime models support decision-making and reasoning for self-adaptation based on both
design-time knowledge and information that may emerge at runtime. In this paper, we …

[Context/Motivation] Decision-making for self-adaptive systems (SAS) requires the runtime
trade-off of multiple non-functional requirements (NFRs) and the costs-benefits analysis of …

A Self-adaptive system (SAS) is required to continuously satisfy its requirements at runtime
under environmental uncertainty. As the run-time context changes, the system may need to …