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.