scholarly journals Research on Artificial Intelligence Ethics Based on the Evolution of Population Knowledge Base

2018 ◽  
pp. 455-464 ◽  
Author(s):  
Feng Liu ◽  
Yong Shi
Keyword(s):  
Artificial Intelligence ◽  
Knowledge Base

scholarly journals A Belief Update System Using an Event Model for Location of People in a Smart Home

2021 ◽  
pp. 17-32
Author(s):  
Marie Bernert ◽  
Fano Ramparany
Keyword(s):  
Artificial Intelligence ◽  
Knowledge Base ◽  
Smart Home ◽  
Current Knowledge ◽  
Sequence Of Events ◽  
New Information ◽  
Event Model ◽  
Location Inference

AbstractArtificial Intelligence applications often require to maintain a knowledge base about the observed environment. In particular, when the current knowledge is inconsistent with new information, it has to be updated. Such inconsistency can be due to erroneous assumptions or to changes in the environment. Here we considered the second case, and develop a knowledge update algorithm based on event logic that takes into account constraints according to which the environment can evolve. These constraints take the form of events that modify the environment in a well-defined manner. The belief update triggered by a new observation is thus explained by a sequence of events. We then apply this algorithm to the problem of locating people in a smart home and show that taking into account past information and move’s constraints improves location inference.

On techniques of expert systems on the example of the Akinator program

2020 ◽  
Vol 25 (2) ◽  
pp. 7-13
Author(s):  
Zhangozha A.R. ◽  
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Neural Networks ◽  
Expert Systems ◽  
Knowledge Base ◽  
Hybrid Systems ◽  
Online Game ◽  
Basic Principles ◽  
The Moment ◽  
Definition Of

On the example of the online game Akinator, the basic principles on which programs of this type are built are considered. Effective technics have been proposed by which artificial intelligence systems can build logical inferences that allow to identify an unknown subject from its description (predicate). To confirm the considered hypotheses, the terminological analysis of definition of the program "Akinator" offered by the author is carried out. Starting from the assumptions given by the author's definition, the article complements their definitions presented by other researchers and analyzes their constituent theses. Finally, some proposals are made for the next steps in improving the program. The Akinator program, at one time, became one of the most famous online games using artificial intelligence. And although this was not directly stated, it was clear to the experts in the field of artificial intelligence that the program uses the techniques of expert systems and is built on inference rules. At the moment, expert systems have lost their positions in comparison with the direction of neural networks in the field of artificial intelligence, however, in the case considered in the article, we are talking about techniques using both directions – hybrid systems. Games for filling semantics interact with the user, expanding their semantic base (knowledge base) and use certain strategies to achieve the best result. The playful form of such semantics filling programs is beneficial for researchers by involving a large number of players. The article examines the techniques used by the Akinator program, and also suggests possible modifications to it in the future. This study, first of all, focuses on how the knowledge base of the Akinator program is built, it consists of incomplete sets, which can be filled and adjusted as a result of further iterations of the program launches. It is important to note our assumption that the order of questions used by the program during the game plays a key role, because it determines its strategy. It was identified that the program is guided by the principles of nonmonotonic logic – the assumptions constructed by the program are not final and can be rejected by it during the game. The three main approaches to acquisite semantics proposed by Jakub Šimko and Mária Bieliková are considered, namely, expert work, crowdsourcing and machine learning. Paying attention to machine learning, the Akinator program using machine learning to build an effective strategy in the game presents a class of hybrid systems that combine the principles of two main areas in artificial intelligence programs – expert systems and neural networks.

Artificial Intelligence in Medical Science

2014 ◽  
pp. 11-23 ◽  
Keyword(s):  
Artificial Intelligence ◽  
Image Processing ◽  
Decision Making ◽  
Signal Processing ◽  
Expert System ◽  
Knowledge Base ◽  
Medical Diagnosis ◽  
Medical Science ◽  
Inference Engine ◽  
Medical Decision

Applying Artificial Intelligence (AI) for increasing the reliability of medical decision making has been studied for some years, and many researchers have studied in this area. In this chapter, AI is defined and the reason of its importance in medical diagnosis is explained. Various applications of AI in medical diagnosis such as signal processing and image processing are provided. Expert system is defined and it is mentioned that the basic components of an expert system are a “knowledge base” or KB and an “inference engine”. The information in the KB is obtained by interviewing people who are experts in the area in question.

Clinical Practice Ontology Automatic Learning from SOAP Reports

2016 ◽  
pp. 349-363
Author(s):  
David Mendes ◽  
Irene Pimenta Rodrigues ◽  
Carlos Fernandes Baeta
Keyword(s):  
Artificial Intelligence ◽  
Clinical Practice ◽  
Natural Language ◽  
Knowledge Base ◽  
Clinical Information ◽  
Knowledge Structure ◽  
Daily Routine ◽  
Automatic Learning ◽  
Controlled Natural Language ◽  
Practice Knowledge

We show how we implemented an end-to-end process to automatically develop a clinical practice knowledge base acquiring from SOAP notes. With our contribution we intend to overcome the “Knowledge Acquisition Bottleneck” problem by jump-starting the knowledge gathering from the most widely available source of clinical information that are natural language reports. We present the different phases of our process to populate automatically a proposed ontology with clinical assertions extracted from daily routine SOAP notes. The enriched ontology becomes a reasoning able knowledge base that depicts accurately and realistically the clinical practice represented by the source reports. With this knowledge structure in place and novel state-of-the-art reasoning capabilities, based in consequence driven reasoners, a clinical QA system based in controlled natural language is introduced that reveals breakthrough possibilities regarding the applicability of Artificial Intelligence techniques to the medical field.

scholarly journals ICAR '96 Conference Highlights - Part 2

1996 ◽  
Vol 1 (3) ◽  
pp. 11-14
Author(s):  
Chris Estey ◽  
Peter Grandsard
Keyword(s):  
Analytical Chemistry ◽  
Artificial Intelligence ◽  
Knowledge Base ◽  
Scientific Session ◽  
Laboratory Medicine ◽  
Laboratory Automation ◽  
International Conference ◽  
Novel Technology ◽  
Sheraton Hotel ◽  
Oral Presentations

The International Conference on Automation, Robotics and Artificial Intelligence Applied to Analytical Chemistry and Laboratory Medicine has become the premier meeting dedicated to expanding the knowledge base in the rapidly evolving field of laboratory automation. This year was the fifth consecutive year for the International Conference, and we experienced impressive growth in registrations and exhibitions. The conference, held at the Sheraton Hotel and Marina in San Diego, California, featured 51 exhibitors, 14 sponsors, 54 oral presentations, 41 posters, and over 600 registrants and exhibitor associates. In the last issue of LAN, we covered the first day of scientific sessions which focused on artificial intelligence as well as the final session on novel technology. In this second part of a three-part article, we summarize Part 1 of the parallel scientific session of the conference.

scholarly journals Rules-Based System for Writing Arabic Numerals in Indonesian Words

2021 ◽  
Vol 12 (4) ◽  
pp. 177-185
Author(s):  
F.X. Wisnu Yudo Untoro
Keyword(s):  
Artificial Intelligence ◽  
Knowledge Base ◽  
Experimental Results ◽  
Rule Based ◽  
Forward Chaining ◽  
Rule Based System ◽  
Arabic Number ◽  
Made In

One of the algorithms stored in natural intelligence is the writing of Arabic numerals in Indonesian words. Algorithms in naturals intelligence are not easy to find. This problem gave us an idea to create artificial intelligence that tries to mimic natural intelligence algorithms. The proposed algorithm for building artificial intelligence is an R-Z rule-based system. This rule-based system contains a knowledge base of R-Z rules and a knowledge base of facts. In the knowledge base, the R-Z rule provides the R rule and the Z rule, while the facts knowledge base provides facts in the form of a definite standard number and an affix word. R-Z rule-based system for reasoning writing Arabic numerals in Indonesian words uses forward chaining. Artificial intelligence designs that mimic naturals intelligence in writing numbers in Indonesian words were made in C using Borland C++ 5.02 software. The experimental results show that by applying the R's rule of seven rules and Z's of twenty-five rules, the R-Z rule-based system can write Arabic numerals in Indonesian words from Arabic numerals "0" to Arabic numerals "9999999". For example, to write the Arabic number "10" in Indonesian words, the R-Z rule-based system starts with the R2 rule. Rule R2 takes action on Z3 to create new facts about Arabic numerals in the Indonesian word, namely "SEPULUH."

scholarly journals Networked Artificial Intelligence English Translation System Based on an Intelligent Knowledge Base and Translation Method Thereof

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Shuping Ren
Keyword(s):  
Artificial Intelligence ◽  
Knowledge Base ◽  
Structure Analysis ◽  
English Translation ◽  
Language Translation ◽  
Translation Method ◽  
Translation System ◽  
Chinese Translation ◽  
Lexical Structure ◽  
Traditional Language

Language translation is often conducted in work and study. Traditional language translation is based on lexical structure analysis. However, natural language is not so standardized, which causes this translation method to have fundamental defects, no matter how much the algorithm is improved. The translation results and human translation will be very different. This paper mainly studies the networked artificial intelligence. The English translation system and translation methods are based on a smart knowledge base. Bringing an example of English-Chinese translation to suggest translations according to the intelligent knowledge base explains in detail the principle of intelligent knowledge-based translation and the advantage of this translation method compared with the traditional translation method based on lexical structure analysis. In the experiment of this paper, when the variance is 2/N, 30/N, 100/N, and 2N, it is the experimental data for an in-depth study. When the variance is 2/N, 30/N, and 100/N, the result is the same as that when the variance is 0.5; the result when the variance is 2N also conforms to the trend in the tables, which is close to the effect of the smoothing algorithm, which verifies the effectiveness of the system in this paper.

scholarly journals Knowledge base of wind farm devices in the computer expert system

2018 ◽  
Vol 67 (2) ◽  
pp. 179-190
Author(s):  
Radosław Duer ◽  
Paweł Wrzesień ◽  
Stanisław Duer ◽  
Dariusz Bernatowicz
Keyword(s):  
Artificial Intelligence ◽  
Expert System ◽  
Knowledge Base ◽  
Wind Farm ◽  
Diagnostic Information ◽  
Diagnostic Model ◽  
Technical Diagnostics ◽  
Wind Power Plant ◽  
Power Plant Equipment ◽  
Plant Equipment

The article presents the problems of determining diagnostic information for the needs of testing the state of wind farm equipment. To this end, the essence of developing a functional and diagnostic model on the example of wind power plant equipment has been presented and described. Based on the developed model of the examined object, diagnostic information was determined in the form of a set of basic elements and a set of diagnostic signals, which are developed by the designated j-elements in the i-functional units of the object. The article presents a description of the process of building a knowledge base for an expert system. Keywords: technical diagnostics, diagnostic reasoning, multivalent logic, artificial intelligence

scholarly journals Development of an Integrated Complex of Knowledge Base and Tools of Expert Systems for Assessing Knowledge of Students in Mathematics within the Framework of a Hybrid Intelligent Learning Environment

2021 ◽  
Vol 15 ◽  
pp. 122-129
Author(s):  
O. V. Druzhinina ◽  
I. A. Karpacheva ◽  
O. N. Masina ◽  
A. A. Petrov
Keyword(s):  
Artificial Intelligence ◽  
Learning Environment ◽  
Knowledge Base ◽  
Educational Process ◽  
Classification Problems ◽  
Creative Potential ◽  
Structural Scheme ◽  
Intelligent Learning Environment ◽  
Mining Methods ◽  
Training Control

The paper is devoted to the development of instrumental and methodological support for the assessment of students' knowledge in mathematics in the framework of a hybrid intellectual learning environment. According to the structural scheme of the model of intellectual assessment of knowledge and creative potential of students in mathematics, the structure of the corresponding knowledge base is formalized. Knowledge base within the framework of data mining methods to create a module for monitoring and evaluating knowledge in mathematics has been developed. To model the educational process the authors propose methods for solving clustering, dimensionality reduction, and classification problems based on machine learning and artificial neural networks. The basics for the development of integrated knowledge base complexes and artificial intelligence tools for the educational process are presented. The obtained results are aimed at creating methods which ensure the processes of operational training, control and evaluation of knowledge.

scholarly journals Ask not what AI can do for art... but what art can do for AI

Artnodes ◽  
2020 ◽  
Author(s):  
Meredith Tromble
Keyword(s):  
Artificial Intelligence ◽  
Knowledge Base ◽  
Contemporary Art ◽  
Thought Experiment ◽  
Embodied Knowledge ◽  
Cultural Positioning ◽  
Limited Scope

What can art do for artificial intelligence? This essay circles around this question from a viewpoint grounded in the embodied knowledge base of contemporary art. The author employs the term “feelthink” to refer to the shifting webs of perception, emotion, thought, and action probed by artists engaging AI. Tracing several metaphors used by artists to consider AI, the author identifies points where the metaphors delaminate, pulling away from the phenomena to which they refer. The author advocates for these partial and imagistic understandings of AI as probes which, despite or because of their flaws, contribute important ideas for the development and cultural positioning of AI entities. The author further questions the limited scope of art ideas addressed in AI research and proposes a thought experiment in which art joins industry as a source of questions for developing artificial intelligences. In conclusion, the essay’s structuring metaphor is described as an example of “feelthink” at work.

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