Seamless Integration of Knowledge Acquisition for Autonomous Systems by Domain Users with Prudence Capability
Technical Report,12 Sep 2016,11 Sep 2018
UNIVERSITY OF TASMANIA Sandy Bay Australia
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Knowledge-based systems are typically constrained by their ability to acquire new knowledge, thus limiting their applicability to autonomous systems. This work developed an extensive, easily maintainable hierarchical Knowledge-base System KBS for Autonomous Systems AS technologies trained by Knowledge Domain Experts KDE using a Natural language NL interface for communication. The system implements an abstracted architecture, taking a layer-based approach to separate data and hardware, information, and services, each with an associated, contextual knowledge base. The developed process, Contextual MCRDR, improves upon classical Multiple Classification Ripple Down Rules MCRDR, with constrained natural language conversation systems associated with querying of in-situ databases of pre-existing information. This was then expanded to support Automatic Speech Recognition ASR. Finally, the work was extended to a semi-autonomous system Robotis Turtlebot3. The full effort produced three published journalconference papers, and two additional papers in the review process.
- Computer Programming and Software