Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2406.17816 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866929400177491968 |
|---|---|
| author | Ramanathan, Ganesh Mayer, Simon Ciortea, Andrei |
| author_facet | Ramanathan, Ganesh Mayer, Simon Ciortea, Andrei |
| contents | Electromechanical systems manage physical processes through a network of inter-connected components. Today, programming the interactions required for coordinating these components is largely a manual process. This process is time-consuming and requires manual adaptation when system features change. To overcome this issue, we use autonomous software agents that process semantic descriptions of the system to determine coordination requirements and constraints; on this basis, they then interact with one another to control the system in a decentralized and coordinated manner.Our core insight is that coordination requirements between individual components are, ultimately, largely due to underlying physical interdependencies between the components, which can be (and, in many cases, already are) semantically modeled in automation projects. Agents then use hypermedia to discover, at run time, the plans and protocols required for enacting the coordination. A key novelty of our approach is the use of hypermedia-driven interaction: it reduces coupling in the system and enables its run-time adaptation as features change. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_17816 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Towards Hypermedia Environments for Adaptive Coordination in Industrial Automation Ramanathan, Ganesh Mayer, Simon Ciortea, Andrei Multiagent Systems Artificial Intelligence Electromechanical systems manage physical processes through a network of inter-connected components. Today, programming the interactions required for coordinating these components is largely a manual process. This process is time-consuming and requires manual adaptation when system features change. To overcome this issue, we use autonomous software agents that process semantic descriptions of the system to determine coordination requirements and constraints; on this basis, they then interact with one another to control the system in a decentralized and coordinated manner.Our core insight is that coordination requirements between individual components are, ultimately, largely due to underlying physical interdependencies between the components, which can be (and, in many cases, already are) semantically modeled in automation projects. Agents then use hypermedia to discover, at run time, the plans and protocols required for enacting the coordination. A key novelty of our approach is the use of hypermedia-driven interaction: it reduces coupling in the system and enables its run-time adaptation as features change. |
| title | Towards Hypermedia Environments for Adaptive Coordination in Industrial Automation |
| topic | Multiagent Systems Artificial Intelligence |
| url | https://arxiv.org/abs/2406.17816 |