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Prof. Dr. S. Decker
RWTH Aachen
Informatik 5
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Knowledge-based Bot Configurator

Thesis type
  • Bachelor
  • Master
Status Open
Supervisor(s)
Advisor(s)

Whether it's customer support, surveys or a simple chatbot, there's no need to reinvent the wheel. Creating bots should be easy. This thesis will implement a configurator for (chat)bots by utilizing the social bot framework and bot blueprints. The result of the thesis should be a template library offering different social bot types (e.g. chatbots, crawlers, transactional bots or informational bots) that can be configured.

In our efforts to support heterogeneous communities with the tools and structures they need, we created our flagship peer-to-peer community platform las2peer. In our latest research efforts, we developed a social bot framework, which allows for a model-driven collaborative construction and utilization of social bots in the domain of technology enhanced learning (TEL). With the latest enhancements, it is possible to create bots via modeling (utilizing templates) or through a conversation with a chatbot. By providing templates and services, it is often unclear whether these resources can be trusted. For this purpose, a blockchain can be used to verify these templates. Likewise, other metrics can be used to inspire trust in the provision of such templates.

 

The goal of this thesis is to create a community-driven knowledge-based configurator for social bots. Additionally, the framework should be evaluated using existing, las2peer powered, community applications (e.g. the MobSOS).

If you are interested in this thesis, please do not hesitate to send a message to  neumann@dbis.rwth-aachen.de.

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