Learning Mechanisms on OWL-S Service Descriptions for Automated Service Selection

Abstract

With the increase complexity of IoT systems, the well known development paradigm for software development like Service Oriented Architectures and Multi Agent Systems have to be adapted to t the now challenges of IoT environments. Here the vast amount of available components and the speci c implementation for special purpose hardware calls for an abstraction of functionality as well as to new development tools which allow to handle the dynamism of IoT applications. Here a multitude of special purpose sensors with view computational resources have to be combined to create emerging software. Most of the hardware reaches an return of investment only o ering its service to third party developers. For a developer to be able to integrate those services into an application, a adaptive search mechanism need to be developed, which is able to specialize in the di erent domains of e.g. IoT applications.

@article{fahndrich2017,
  title={Learning Mechanisms on OWL-S Service Descriptions for Automated Action Selection},
  author={F{"a}hndrich, Johannes and Masuch, Nils and Borchert, Lars and Albayrak, Sahin},
  journal={IoA17 at 16th International Conference on Autonomous Agents and Multiagent Systems AAMAS},
  pages={56 -- 73},
  year={2017}
}
Authors:
Johannes Fähndrich, Nils Masuch, Lars Borchert, Sahin Albayrak
Category:
Conference Paper
Year:
2017
Location:
16th International Conference on Autonomous Agents and Multiagent Systems (AAMAS)