Gaining Knowledge Through Experience: Developing Decisional Dna Applications in Robotics

Abstract

In this article, we explore an approach that integrates Decisional DNA, a domain-independent, flexible, and standard knowledge representation structure, with robots in order to test the usability and suitability of this novel knowledge representation structure. Core issues in using this Decisional DNA-based method include capturing of knowledge, storage and indexing of knowledge, organization of the knowledge base memory, and retrieval of knowledge from memory according to current problems. We demonstrate our approach in a set of experiments in which the robots capture knowledge from their tasks and are able to reuse such knowledge in subsequent tests.

Closed-Loop-Engineering – enabler for swift reconfiguration in plant engineering

“…VEO is developed on the concept of cradle-to-grave approach, which means that the contextual information and decision-making regarding an engineering object right for its inception until its useful life is stored or linked in it. The knowledge representation technique of Set of experience knowledge structure (SOEKS) and Decisional DNA (DDNA) ( (Sanin Szczerbicki 2005, Sanin et al 2007, Zhang et al 2010 is used for developing this model. SOEKS-DDNA provides dynamicity to VEO to overcome issues related to representation of complex and discrete objects (Shafiq et al 2014b).…”