Ganesh Ramanathan
Title
Dr.
Last Name
Ramanathan
First name
Ganesh
Email
ganesh.ramanathan@unisg.ch
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Item type:Publication, Towards Hypermedia Environments for Adaptive Coordination in Industrial AutomationElectromechanical systems manage physical processes through a network of interconnected components. Today, programming the interactions required for coordinating these components is largely a manual process. This process is timeconsuming 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.Type:conference paperJournal:2024 IEEE 29th International Conference on Emerging Technologies and Factory Automation (ETFA)Scopus© Citations 4 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, HyperBrain: Human-inspired Hypermedia Guidance using a Large Language Model(ACM, 2023-09-05); ; ; ; We present HyperBrain, a hypermedia client that autonomously navigates hypermedia environments to achieve user goals specified in natural language. To achieve this, the client makes use of a large language model to decide which of the available hypermedia controls should be used within a given application context. In a demonstrative scenario, we show the client's ability to autonomously select and follow simple hyperlinks towards a high-level goal, successfully traversing the hypermedia structure of Wikipedia given only the markup of the respective resources. We show that hypermedia navigation based on language models is effective, and propose that this should be considered as a step to create hypermedia environments that are used by autonomous clients alongside people.Type:conference paperScopus© Citations 5