Engineering Background Knowledge For Social Robots

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Engineering Background Knowledge for Social Robots

Engineering Background Knowledge for Social Robots
Author :
Publisher : IOS Press
Total Pages : 240
Release :
ISBN-10 : 9781643681092
ISBN-13 : 1643681095
Rating : 4/5 (095 Downloads)

Book Synopsis Engineering Background Knowledge for Social Robots by : L. Asprino

Download or read book Engineering Background Knowledge for Social Robots written by L. Asprino and published by IOS Press. This book was released on 2020-09-25 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: Social robots are embodied agents that perform knowledge-intensive tasks involving several kinds of information from different heterogeneous sources. This book, Engineering Background Knowledge for Social Robots, introduces a component-based architecture for supporting the knowledge-intensive tasks performed by social robots. The design was based on the requirements of a real socially-assistive robotic application, and all the components contribute to and benefit from the knowledge base which is its cornerstone. The knowledge base is structured by a set of interconnected and modularized ontologies which model the information, and is initially populated with linguistic, ontological and factual knowledge retrieved from Linked Open Data. Access to the knowledge base is guaranteed by Lizard, a tool providing software components, with an API for accessing facts stored in the knowledge base in a programmatic and object-oriented way. The author introduces two methods for engineering the knowledge needed by robots, a novel method for automatically integrating knowledge from heterogeneous sources with a frame-driven approach, and a novel empirical method for assessing foundational distinctions over Linked Open Data entities from a common-sense perspective. These effectively enable the evolution of the robot’s knowledge by automatically integrating information derived from heterogeneous sources and the generation of common-sense knowledge using Linked Open Data as an empirical basis. The feasibility and benefits of the architecture have been assessed through a prototype deployed in a real socially-assistive scenario, and the book presents two applications and the results of a qualitative and quantitative evaluation.


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