Narendra, Nanjangud and Nagaraj, Nithin
(2026)
Intent-Driven Modeling and
Management of Complex Adaptive
Systems – Proposed Approach and
Research Agenda.
preprints.org.
(Submitted)
![[img]](http://eprints.nias.res.in/style/images/fileicons/text.png) |
Text
Intent-Driven Modeling and.pdf
- Submitted Version
Download (1MB)
|
| Abstract: |
Complex adaptive systems (CAS) have two defining characteristics. First, they are complex, i.e.,
composed of several interacting parts. Second, they are adaptive, i.e., their behavior can be changed
in response to external stimuli and changes in the external environment. Due to this, managing such
systems is quite challenging. Traditional approaches have involved defining policies that determine
the behavior of any CAS under particular circumstances. However, such approaches are rigid and
inflexible, since they are dependent on pre-specified policies. To that end, in this position paper, we
describe an intent-driven approach to modeling and managing CAS. This would be a more flexible
approach, not dependent on any specific policies, but which can be customized based on the context in
which the CAS is functioning. We describe the various components of our approach, which include
compositional reasoning to decompose the intent into sub-intents as per the context; mapping the
sub-intents onto the execution model which will satisfy the intent; and feeding back the results of
the execution to facilitate continual learning and continuous improvement in managing the CAS. In
particular, one aspect that we highlight is the application of neurochaos learning, which uses chaos
theory to facilitate rapid continual learning that would help improve the overall efficiency of our
approach. For each component of our approach, we also present several research questions that need
to be addressed before intent-driven management of CAS can become a reality |
| Item Type: |
Journal Paper
|
| Keywords: |
complex adaptive systems; knowledge graphs; compositional reasoning; intent-driven
management; intent decomposition |
| Subjects: |
School of Natural and Engineering Sciences > Complex Systems |
| Divisions: |
Schools > Natural Sciences and Engineering |
| Date Deposited: |
20 May 2026 11:07 |
| Last Modified: |
20 May 2026 11:07 |
| Official URL: |
https://www.preprints.org/manuscript/202605.0367 |
| Related URLs: |
|
| Funders: |
* |
| Projects: |
* |
| DOI: |
10.20944/preprints202605.0367.v1 |
| URI: |
http://eprints.nias.res.in/id/eprint/3345 |
Actions (login required)
 |
View Item |
