Defining adaption measures for organisational multi-agent systems

Abstract

Designing adaptive multi-agent Systems (MAS) is a challenging development effort. A key point of adaptive systems is that they provide alternative options for acting and designers have to weight the number and elaboration of these alternatives. Here, we concentrate on organisation-oriented MAS and show that organisational models provide suitable means for identifying key measures of this adaptivity. We derive measures both from the static description of the organisation as well as from the induced adaptation dynamics grounded on  a Markovian analysis of the behaviour. These measures allow for a goal-directed planning of adaption.

Keywords:

• Complex adaptive systems
• multi-agent systems
• organisation-oriented design
• MAPE-loop
• [email protected]
• Petri nets

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 If we want to express this aspect, we have to replace the absolute option value ${\mathit{O}\mathit{p}\mathit{t}}_p$ in (1(1) $\mathit{C}\mathit{o}\mathit{n}\mathit{t}\mathit{i}\mathit{n}\mathit{g}\mathit{e}\mathit{n}\mathit{c}\mathit{y}\left(G\right):=E\left[{\mathit{O}\mathit{p}\mathit{t}}_p\right]=\frac{1}{|P_G|}\cdot \sum _{p\in P\left(G\right)}{\mathit{O}\mathit{p}\mathit{t}}_p$(1) ) by a value weighted with the distance of the task p from G's initial task $p_0$, i.e.${\gamma }^{\mathit{d}\mathit{i}\mathit{s}\mathit{t}(p_0,p)}\cdot {\mathit{O}\mathit{p}\mathit{t}}_p$ where $\gamma \in [0;1]$ is a decay factor.