DOCSLIB.ORG

Function Knowledge Retrieval Based on Functions Knowledge Ontology

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Function Knowledge Retrieval Based on Functions Knowledge Ontology International Conference on Civil, Materials and Environmental Sciences (CMES 2015) Function Knowledge Retrieval Based on Functions Knowledge Ontology 1,a 1,b Baoru Su , Yong Liu 1 The College of Information Science and Technology, Qingdao University of Science & Technology, Qingdao 266061, Shandong, China [email protected],[email protected] product principle solution. Abstract—It has been found that design knowledge y Structure knowledge: management is facing many problems in product design. In It is used to describe the structure design of products, it order to improve the design of knowledge sharing and is the refinement and expansion of principle, it is the reusability, the research of function knowledge ontology model structure carrier of theory of solving domain, and it is used has been carried out, which include extended device ontology to describe the shape, size and parameters of the key parts and way of function achievement. Based on the combination of the product. above a refrigerator function ontology and function Mapping of product function and structure is solving decomposition tree has been set up. Function knowledge structure to achieve the function model of product; the retrieval on constructing the function ontology has been functional description of product will be changed to the implemented. A software platform for sharing knowledge description of how to realize these functions with the function decomposition tree has been designed. specific switch, size and the relationship between the parts of components. Keywords- Function knowledge ontology; Manufacturing; The objective of structure realization is Abstraction of Knowledge representation; Function decomposition tree the product structure; and the structure is a set of I. INTRODUCTION components or elements to realize some functions. The mapping relationship between function and structure is Product design is a key stage to determine product many-to-many. A function may be implemented by one or success. However, design knowledge management is facing more features or components, and a feature or element may many problems now. The current situation of design also be performing one or more functions. knowledge expression is as following: y Examples knowledge. y The designer access difficulties. Failure examples of the design, including the scheme y Searching for many documents, the manuals design cases, the product structure knowledge examples, and data occurred in the development technical theory examples and so on. It contains more actual process is time-consuming, and the text factors, and it is foundation of the analog design and case based reasoning design. data about description of concept is Function ontology theory is applied to manufacturing disunity, no semantic expression, it is industry in this paper, function knowledge modeling difficult for computer to understand. method is studied, theory system and construction method y Capture of implicit knowledge is not easy. of function concept ontology are introduced, and the Main reason for the above problems lies in the principle of functional decomposition tree is introduced as understanding insufficiency of the function of generating well. aspect, thus leading to the different views about object This paper draws the function ontology theory presented world in different application fields and the lack of by Mizoguchi lab of the Osaka University in Japan, consistency in the function of knowledge account. In order Ontology is introduced in the home appliance to achieve the knowledge sharing and reuse in different manufacturing industry (refrigerator as an example), so that field, the function knowledge ontology framework is used an accurate, efficient, and intelligent retrieval of function in design. knowledge is implemented. In the design activities, the design knowledge mainly II FUNCTION ONTOLOGY including: y Function knowledge: Functional ontology is proposed based on studying It is used to describe the tasks of products, describe the about ontology, ontology in the application of knowledge functions and sub functions of product. Function description engineering and F-B-S architecture. At present, no one does includes content of function, the implementation parameters further research in this field in China, only a few scholars of function, performance index of function and so on. who have done some research of computer integrated y Technical theory knowledge. manufacturing technology tried to use ontology to solve Describe the principle of product functions and sub some product knowledge representation and information functions. Its expression is more complicated, on one hand; modeling, representatives are as follows: its description can be expressed in text, data and parameters Dr. Li Jian of Beijing University of Aeronautics and explanation, on the other hand, to have graphics support Astronautics [1] put forward the concept of principle © 2015. The authors - Published by Atlantis Press 596 component and functional connectivity through the analysis representation, proposes the conceptual design product of the function of the product element, working principle information modeling method based on ontology. and components of functional surfaces, and set up product Above scholars’ Research only remain in the application principle structure model on this basis using object oriented field; no one has done some research in theory field in method, product design process model based on function China. In abroad, the representative research institution are given as well. about function of Ontology is Mizoguchi Research Dr. Shi Dongyan of Harbin Institute of Technology [2], Laboratory of Osaka University in Japan. They made a deep put forward the concept of design process based on function study of the ontology and F-B-S schema, and successfully through the analysis of the research and application of applied in the manufacturing field, presents a hierarchical conceptual design process theory, studies the application of framework of ontology, knowledge and the function model ontology knowledge in conceptual design process by [4][5] as Figure 1, they studied the function and the referencing ontology. Through the analysis of existing function concept around the center of equipment and put problems in function definition, proposed the function can forward FTs and FBRL[6] in order to realize the function be expressed using the function of semantic; proposed uses behavior mapping. Their research has been successfully the ontology theory to establish the conceptual design applied to engineering, chemical plants, oil refineries, solving process of domain knowledge. Associate professor power plants, washing machine and transistor factory and Wang Youyuan of the Nanjing University of Aeronautics & other fields, design and implementation of knowledge Astronautics [3], realize the share and reuse the design sharing and reuse are achieved. knowledge through the research of conceptual design product information modeling. Analysis of the F-B-S framework of information of product conceptual design Top level ontology Basic principle Equipment body expansion General concept Functional concept ontology Common knowledge Function method of knowledge Attribute tree of The general functional Depending on the context method decomposition tree Specific items Functional decomposition tree Figure 1. Hierarchy framework of Function, Knowledge and Ontology To sum up, the function ontology is based on the decomposition tree contains the design concept and design ontology principle, achieving Standardization of function principle of equipment; and because the function concept knowledge in conceptual design field of products, so as to came from functional concept ontology, so the problem of effectively share the function knowledge, and realize the inconsistent terminology is solved. If the engineer can function knowledge reusability. The function ontology express design principle of equipment using functional defines the function space in the conceptual vocabulary to decomposition tree after the completion of the design, then specifications and limited function space. Function concept it is easy to realize the sharing of design knowledge. In this of application in ontology enables designers to better paper, the design and implementation of ontology based understand the design demand and effective reasoning in retrieval function are achieved, Firstly create the ontology function space. library, and then the Jena inference engine reasoning according to reasoning rules designed, system is expected to III APPLICATION OF FUNCTION ONTOLOGY IN THE FIELD OF achieve a relevant function of the retrieval platform. Users HOME APPLIANCES only need to input the query component function, and get a component with the function, users also can search all the A Design functions of a member, user can also retrieve a method of Through the research and analysis on the function function realization, agent and the entity function through knowledge framework, we found that functional this platform. The system integrated three body mentioned 597 in reference [4][5] into one body, which is conducive to the In this paper, the scientific research as a target, with ontology query. concise, avoid unnecessary redundancy and convenient for extracting the operable principle, borrowing the function B The construction of function ontology ontology framework proposed by Mizoguchi lab, according In a previous study, the ontology frame is built by Hozo to the
Load more

Recommended publications
  • Artificial Intelligence in Health Care: the Hope, the Hype, the Promise, the Peril
    Artificial Intelligence in Health Care: The Hope, the Hype, the Promise, the Peril Michael Matheny, Sonoo Thadaney Israni, Mahnoor Ahmed, and Danielle Whicher, Editors WASHINGTON, DC NAM.EDU PREPUBLICATION COPY - Uncorrected Proofs NATIONAL ACADEMY OF MEDICINE • 500 Fifth Street, NW • WASHINGTON, DC 20001 NOTICE: This publication has undergone peer review according to procedures established by the National Academy of Medicine (NAM). Publication by the NAM worthy of public attention, but does not constitute endorsement of conclusions and recommendationssignifies that it is the by productthe NAM. of The a carefully views presented considered in processthis publication and is a contributionare those of individual contributors and do not represent formal consensus positions of the authors’ organizations; the NAM; or the National Academies of Sciences, Engineering, and Medicine. Library of Congress Cataloging-in-Publication Data to Come Copyright 2019 by the National Academy of Sciences. All rights reserved. Printed in the United States of America. Suggested citation: Matheny, M., S. Thadaney Israni, M. Ahmed, and D. Whicher, Editors. 2019. Artificial Intelligence in Health Care: The Hope, the Hype, the Promise, the Peril. NAM Special Publication. Washington, DC: National Academy of Medicine. PREPUBLICATION COPY - Uncorrected Proofs “Knowing is not enough; we must apply. Willing is not enough; we must do.” --GOETHE PREPUBLICATION COPY - Uncorrected Proofs ABOUT THE NATIONAL ACADEMY OF MEDICINE The National Academy of Medicine is one of three Academies constituting the Nation- al Academies of Sciences, Engineering, and Medicine (the National Academies). The Na- tional Academies provide independent, objective analysis and advice to the nation and conduct other activities to solve complex problems and inform public policy decisions.
    [Show full text]
  • Automatic Knowledge Retrieval from the Web
    Automatic Knowledge Retrieval from the Web Marcin Skowron and Kenji Araki Graduate School of Information Science and Technology, Hokkaido University, Kita-ku Kita 14-jo Nishi 8-chome, 060–0814 Sapporo, Japan Abstract. This paper presents the method of automatic knowledge retrieval from the web. The aim of the system that implements it, is to automatically create entries to a knowledge database, similar to the ones that are being provided by the volunteer contributors. As only a small fraction of the statements accessible on the web can be treated as valid knowledge concepts we considered the method for their filtering and verification, based on the similarity measurements with the concepts found in the manually created knowledge database. The results demonstrate that the system can retrieve valid knowledge concepts both for topics that are described in the manually created database, as well as the ones that are not covered there. 1 Introduction Despite the years of research in the field of Artificial Intelligence, the creation of a machine with the ability to think is still far from realization. Although computer systems are capable of performing several complicated tasks that require human beings to extensively use their thinking capabilities, machines still cannot engage into really meaningful conversation or understand what people talk about. One of the main unresolved problems is the lack of machine usable knowledge. Without it, machines cannot reason about the everyday world in a similar way to human beings. In the last decade we have witnessed a few attempts to create knowledge databases using various approaches: man- ual, machine learning and mass collaboration of volunteer contributors.
    [Show full text]
  • Information Extraction Using Natural Language Processing
    INFORMATION EXTRACTION USING NATURAL LANGUAGE PROCESSING Cvetana Krstev University of Belgrade, Faculty of Philology Information Retrieval and/vs. Natural Language Processing So close yet so far Outline of the talk ◦ Views on Information Retrieval (IR) and Natural Language Processing (NLP) ◦ IR and NLP in Serbia ◦ Language Resources (LT) in the core of NLP ◦ at University of Belgrade (4 representative resources) ◦ LR and NLP for Information Retrieval and Information Extraction (IE) ◦ at University of Belgrade (4 representative applications) Wikipedia ◦ Information retrieval ◦ Information retrieval (IR) is the activity of obtaining information resources relevant to an information need from a collection of information resources. Searches can be based on full-text or other content-based indexing. ◦ Natural Language Processing ◦ Natural language processing is a field of computer science, artificial intelligence, and computational linguistics concerned with the interactions between computers and human (natural) languages. As such, NLP is related to the area of human–computer interaction. Many challenges in NLP involve: natural language understanding, enabling computers to derive meaning from human or natural language input; and others involve natural language generation. Experts ◦ Information Retrieval ◦ As an academic field of study, Information Retrieval (IR) is finding material (usually documents) of an unstructured nature (usually text) that satisfies an information need from within large collection (usually stored on computers). ◦ C. D. Manning, P. Raghavan, H. Schutze, “Introduction to Information Retrieval”, Cambridge University Press, 2008 ◦ Natural Language Processing ◦ The term ‘Natural Language Processing’ (NLP) is normally used to describe the function of software or hardware components in computer system which analyze or synthesize spoken or written language.
    [Show full text]
  • Open Mind Common Sense: Knowledge Acquisition from the General Public
    Open Mind Common Sense: Knowledge Acquisition from the General Public Push Singh, Grace Lim, Thomas Lin, Erik T. Mueller Travell Perkins, Mark Tompkins, Wan Li Zhu MIT Media Laboratory 20 Ames Street Cambridge, MA 02139 USA {push, glim, tlin, markt, wlz}@mit.edu, [email protected], [email protected] Abstract underpinnings for commonsense reasoning (Shanahan Open Mind Common Sense is a knowledge acquisition 1997), there has been far less work on finding ways to system designed to acquire commonsense knowledge from accumulate the knowledge to do so in practice. The most the general public over the web. We describe and evaluate well-known attempt has been the Cyc project (Lenat 1995) our first fielded system, which enabled the construction of which contains 1.5 million assertions built over 15 years a 400,000 assertion commonsense knowledge base. We at the cost of several tens of millions of dollars. then discuss how our second-generation system addresses Knowledge bases this large require a tremendous effort to weaknesses discovered in the first. The new system engineer. With the exception of Cyc, this problem of scale acquires facts, descriptions, and stories by allowing has made efforts to study and build commonsense participants to construct and fill in natural language knowledge bases nearly non-existent within the artificial templates. It employs word-sense disambiguation and intelligence community. methods of clarifying entered knowledge, analogical inference to provide feedback, and allows participants to validate knowledge and in turn each other. Turning to the general public 1 In this paper we explore a possible solution to this Introduction problem of scale, based on one critical observation: Every We would like to build software agents that can engage in ordinary person has common sense of the kind we want to commonsense reasoning about ordinary human affairs.
    [Show full text]
  • Intelligent Technique to Accomplish a Effective Knowledge Retrieval from Distributed Repositories
    INTELLI 2014 : The Third International Conference on Intelligent Systems and Applications Intelligent Technique to Accomplish a Effective Knowledge Retrieval from Distributed Repositories. Antonio Martín, Carlos León Department of Electronic Technology Higher Technical School of Computer Engineering Sevilla, Spain [email protected], [email protected] Abstract— Currently, an enormous quantity of heterogeneous the semantic and Artificial Intelligence (AI) issues from the and distributed information is stored in the current digital whole life cycle and architecture point of view [1]. Our work libraries. Access to these collections poses a serious challenge, differs from related projects in that we build ontology-based however, because present search techniques based on manually contextual profiles and we introduce an approaches used annotated metadata and linear replay of material selected by metadata-based in ontology search and expert systems [2]. the user do not scale effectively or efficiently to large We study improving the efficiency of search methods to collections. The Artificial Intelligence and Semantic Web search a distributed data space like a DL. The objective has provide a common framework that allows knowledge to be focused on creating technologically complex environments shared and reused. In this paper, we propose a comprehensive in Education, Learning and Teaching in the DL domain. We approach for discovering information objects in large digital presented an intelligent approach to develop an efficient collections based on analysis of recorded semantic metadata in those objects and the application of expert system technologies. semantic search engine. It incorporates semantic Web and AI We suggest a conceptual architecture for a semantic and technologies to enable not only precise location of DL intelligent search engine.
    [Show full text]
  • Knowledge Management Design Using Collaborative Knowledge Retrieval Function
    The Asian Journal of Technology Management Vol. 1 No. 2 (2009) 58-70 Knowledge Management Design Using Collaborative Knowledge Retrieval Function Kadarsah Suryadi1*, Cahyono Sigit Pramudyo2 1Industrial Engineering Department, Bandung Institute of Technology, Indonesia 2Industrial Engineering Department, ―Sunan Kalijaga‖ State Islamic University of Yogyakarta, Indonesia ABSTRACT Knowledge is a key word in the information age. Organizational knowledge provides businesses with a way to compete effectively and efficiently in the market. The performance of many organizations is determined more by their knowledge than their physical assets. Capturing and representing knowledge is critical in knowledge management. The spread of organizational knowledge has made a difficulty in sharing knowledge. This problem creates a longer learning cycle. This research proposes a web based knowledge map, using collaborative knowledge retrieval function, as a tool to represent and share knowledge. First, knowledge map gives a comprehensive understanding about what knowledge is needed to achieve objectives, what knowledge sources are available, and which knowledge sources are used by whom. Second, web facilitates knowledge sharing. Third, collaborative knowledge retrieval function will shorten learning cycle. Fourth, the proposed tool is applied to build a web based knowledge for an academic system in higher education. The result of this research is a design of web based knowledge map using collaborative knowledge retrieval function. Collaborative retrieval knowledge function gives recommendations of relevant knowledge between web documents. The proposed model contributes in shortening the learning cycle. Keywords: Knowledge map, Collaborative retrieval knowledge function, Web, Learning cycle, Knowledge Sharing. Introduction* performance of many organizations is determined more by their knowledge than their Knowledge is a key word in the physical assets.
    [Show full text]
  • A Method of Knowledgebase Curation Using RDF Knowledge Graph and SPARQL for a Knowledge-Based Clinical Decision Support System
    347 A method of knowledgebase curation using RDF Knowledge Graph and SPARQL for a knowledge-based clinical decision support system Xavierlal J Mattam and Ravi Lourdusamy Sacred Heart College(Autonomous), Tirupattur, Tamil Nadu, India Abstract Clinical decisions are considered crucial and lifesaving. At times, healthcare workers are overworked and there could be lapses in judgements or decisions that could lead to tragic consequences. The clinical decision support systems are very important to assist heath workers. But in spite of a lot of effort in building a perfect system for clinical decision support, such a system is yet to see the light of day. Any clinical decision support system is as good as its knowledgebase. So, the knowledgebase should be consistently maintained with updated knowledge available in medical literature. The challenge in doing it lies in the fact that there is huge amount of data in the web in varied format. A method of knowledgebase curation is proposed in the article using RDF Knowledge Graph and SPARQL queries. Keywords Clinical Decision Support System, RDF Knowledge Graph, Knowledgebase Curation. 1. Introduction and awareness in the diagnosis and treatment of the disease. Although there were many breakthroughs published in medical literature Decision Support has been a crucial part of globally, down-to-earth use of any of them were a healthcare unit. In every area of a health care slow and far-between. It would have not been facility, critical and urgent decisions have to be the case had there been CDSS that was capable made. In such extreme situations, leaving lives of automatically acquiring reliable knowledge at stake totally to mere human knowledge and from authenticated medical literature.
    [Show full text]
  • The Role of Artificial Intelligence (AI) in Adaptive Elearning System (AES) Content Formation: Risks and Opportunities Involved
    13th International Conference & Exhibition on ICT for Education, Training & Skills Development. ELearning Africa, Kigali Rwanda, September 26 - 28 2018. The Role of Artificial Intelligence (AI) in Adaptive eLearning System (AES) Content Formation: Risks and Opportunities involved. Suleiman Adamu1, Jamilu Awwalu2 1Information and Communications Technology Unit, Sule Lamido University Kafin Hausa, Jigawa State, Nigeria. 2Department of Computer Science, Faculty of Computing and Applied Sciences, Baze University Abuja, Nigeria. [email protected],[email protected] Abstract Artificial Intelligence (AI) plays varying roles in supporting both existing and emerging technologies. In the area of Learning and Tutoring, it plays key role in Intelligent Tutoring Systems (ITS). The fusion of ITS with Adaptive Hypermedia and Multimedia (AHAM) form the backbone of Adaptive eLearning Systems (AES) which provides personalized experiences to learners. This experience is important because it facilitates the accurate delivery of the learning modules in specific to the learner’s capacity and readiness. AES types vary, with Adaptive Web Based eLearning Systems (AWBES) being the popular type because of wider access offered by the web technology.The retrieval and aggregation ofcontents for any eLearning system is critical whichis determined by the relevance of learning material to the needs of the learner.In this paper, we discuss components of AES, role of AI in AES content aggregation, possible risks and available opportunities. Keywords Artificial Intelligence, Adaptive eLearning Systems, Personalized Learning, Intelligent Tutoring Systems Introduction The Internet contains several categories of materials, some of which can be used as educational resources. These educational resources can be retrieved for content formation of Adaptive eLearning Systems (AES).
    [Show full text]
  • A Review of Ontology-Based Information Retrieval Techniques on Generic Domains
    International Journal of Applied Information Systems (IJAIS) – ISSN : 2249-0868 Foundation of Computer Science FCS, New York, USA Volume 12 – No. 13, May 2018 – www.ijais.org A Review of Ontology-based Information Retrieval Techniques on Generic Domains Ishaq Oyebisi Oyefolahan Enesi Femi Aminu Muhammad Bashir Abdullahi Federal University of Technology, Federal University of Technology, Federal University of Technology, Minna, Nigeria Minna, Nigeria Minna, Nigeria Information & Media Technology Computer Science Department Computer Science Department Department Muhammadu Tajudeen Salaudeen Federal University of Technology, Minna, Nigeria Crop Production Department ABSTRACT attributed to the fact that the mechanism to retrieve relevant A promising evolution of the existing web where machine and results that satisfy user’s needs becomes a challenge as a people are in cooperation is the Semantic Web. That is, a result of word mismatch and short queries; in other words, machine’s represented and understandable web. This is ambiguous nature of the natural languages [1]. Thus, in order against the existing web which is syntactic in nature - where for the web to be meaningful both in terms of structure and meaning of query search and its expected results on the web is retrieving relevant information, the web must be understood mostly understood and interpreted by user not machine. and interpreted by both user and machine hence, the term However, the technologies drive behind this goal of semantic semantic web. web is on one hand ontologies and on the other hand information retrieval techniques. Ontology is a data modeling Semantic web is a promising evolution of the existing web technique for structured data repository premised on where machine and people are in cooperation [2].
    [Show full text]
  • A Survey on Retrieval of Mathematical Knowledge
    A Survey on Retrieval of Mathematical Knowledge⋆ Ferruccio Guidi, Claudio Sacerdoti Coen Department of Computer Science and Engineering – DISI University of Bologna {ferruccio.guidi,claudio.sacerdoticoen}@unibo.it Abstract. We present a short survey of the literature on indexing and retrieval of mathematical knowledge, with pointers to 72 papers and tentative taxonomies of both retrieval problems and recurring techniques. 1 Purpose Driven Taxonomy of Retrieval Problems Retrieval of mathematical knowledge is always presented as the low hanging fruit of Mathematical Knowledge Management, and it has been addressed in several papers by people coming either from the formal methods or from the information retrieval community. The problem being resistant to classical content search techniques [LRG13], it is usually addressed combining a small set of new ideas and techniques that are recurrent in the literature. Despite the amount of work, however, there is not a single solution that is the clearly winning on the others, nor convincing unbiased benchmarks to compare solutions. Some authors like [KK07] also suggest that the community should first better understand the actual needs of mathematicians from an unbiased perspective to improve the MKM technology as a whole. In this paper we collect a hopefully comprehensive bibliography, and we roughly classify the papers according to novel taxonomies both for the problems and the techniques employed. The only other surveys on the same topic are [AZ04], now outdated and focused mostly on (European) research projects that contributed to the topic in the 6th Framework Programme, [ZB12], which covers less literature in much greater detail without attempting a classification, [L13],´ which is focused on evaluation of mathematics retrieval, and [L10],´ which is written in Slovak.
    [Show full text]
  • Approaches for Web Search User Interfaces How to Improve the Search Quality for Various Types of Information
    Volume 1, Number 1, December 2010 Journal of Convergence Approaches for Web Search User Interfaces How to improve the search quality for various types of information Evgeny Pyshkin, Andrey Kuznetsov Dept. of Computer Systems and Software Engineering Saint-Petersburg State Polytechnical University Saint-Petersburg, Russian Federation [email protected] Abstract— This paper describes approaches used by web search assist in finding music, images, video, or other types of tools to communicate with users. With respect to different kinds information generally called non-classical search problems. of information resources, we examine interactive interfaces that use textual queries, tag-focused navigation, hyperlink navigation, II. WEB SEARCH USER INTERFACE: TYPES AND SITES visual features, etc. Among others, we introduce the design vision There are at least three aspects that relate to good search and describe the implementation of a visual-interface based on system construction: concepts of query token network and the WordNet ontology. • Using good searching algorithms. Keywords- web search; search problems; query modification; synsets; ontology; WordNet • Implementing intelligent interactive tools supporting query refinement by expansion or modification. I. INTRODUCTION • Providing a friendly and flexible user interface Following Guha et al., there are two major forms of search: assisting users in the process of navigational searching. research and navigation [1]. In research search, the search engine input is some phrase request. The research searching This paper is not focussed on algorithms and search engines, process is usually aimed to locate a number of documents so special attention is paid to user-oriented issues. containing information that users are trying to find (e.g.
    [Show full text]
  • Towards a Brain Inspired Model of Self-Awareness for Sociable Agents
    Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17) Towards a Brain Inspired Model of Self-Awareness for Sociable Agents Budhitama Subagdja Ah-Hwee Tan Joint NTU-UBC Research Centre of Excellence School of Computer Science and Engineering in Active Living for the Elderly (LILY) Nanyang Technological University, Singapore Nanyang Technological University, Singapore e-mail: [email protected] e-mail: [email protected] Abstract of self-awareness mostly focus on modeling specific self- embodiment at the physical aspect (Bongard, Zykov, and Self-awareness is a crucial feature for a sociable agent or robot to better interact with humans. In a futuristic scenario, Lipson 2006; Hart and Scasselati 2012; Stoytchev 2011) to a conversational agent may occasionally be asked for its own recognize and map one’s self in the mirror (Hart and Scasse- opinion or suggestion based on its own thought, feelings, or lati 2012; Stoytchev 2011) or to robustly control one’s move- experiences as if it is an individual with identity, personality, ment regardless physical damages or impairments (Bongard, and social life. In moving towards that direction, in this pa- Zykov, and Lipson 2006). A higher level model of self- per, a brain inspired model of self-awareness is presented that awareness has also been proposed that covers the social as- allows an agent to learn to attend to different aspects of self pect of the robot, but it is made only to deal with a specific as an individual with identity, physical embodiment, mental task of epistemic logical reasoning (Bringsjord et al.
    [Show full text]