Artificial intelligence and content analysis

1988 ◽  
Vol 22 (1) ◽  
pp. 65-97 ◽  
Author(s):  
Jan J. van Cuilenburg ◽  
Jan Kleinnijenhuis ◽  
Jan A. de Ridder
Keyword(s):  
Artificial Intelligence ◽  
Content Analysis

APPLICATION OF ARTIFICIAL INTELLIGENCE TECHNIQUES IN MS. PAC-MAN GAME: A REVIEW

2015 ◽  
Vol 3 (1) ◽  
Author(s):  
Tse Guan Tan ◽  
Jason Teo
Keyword(s):  
Artificial Intelligence ◽  
Content Analysis ◽  
Video Games ◽  
Analysis Method ◽  
Engineering Economics ◽  
Game Ai ◽  
Content Analysis Method ◽  
Wide Range ◽  
Computer Based ◽  
Future Direction

AbstrakTeknik Kecerdasan Buatan (AI) berjaya digunakan dan diaplikasikan dalam pelbagai bidang, termasukpembuatan, kejuruteraan, ekonomi, perubatan dan ketenteraan. Kebelakangan ini, terdapat minat yangsemakin meningkat dalam Permainan Kecerdasan Buatan atau permainan AI. Permainan AI merujukkepada teknik yang diaplikasikan dalam permainan komputer dan video seperti pembelajaran, pathfinding,perancangan, dan lain-lain bagi mewujudkan tingkah laku pintar dan autonomi kepada karakter dalampermainan. Objektif utama kajian ini adalah untuk mengemukakan beberapa teknik yang biasa digunakandalam merekabentuk dan mengawal karakter berasaskan komputer untuk permainan Ms Pac-Man antaratahun 2005-2012. Ms Pac-Man adalah salah satu permainan yang digunakan dalam siri pertandinganpermainan diperingkat antarabangsa sebagai penanda aras untuk perbandingan pengawal autonomi.Kaedah analisis kandungan yang menyeluruh dijalankan secara ulasan dan sorotan literatur secara kritikal.Dapatan kajian menunjukkan bahawa, walaupun terdapat berbagai teknik, limitasi utama dalam kajianterdahulu untuk mewujudkan karakter permaianan Pac Man adalah kekurangan Generalization Capabilitydalam kepelbagaian karakter permainan. Hasil kajian ini akan dapat digunakan oleh penyelidik untukmeningkatkan keupayaan Generalization AI karakter permainan dalam Pasaran Permainan KecerdasanBuatan. Abstract Artificial Intelligence (AI) techniques are successfully used and applied in a wide range of areas, includingmanufacturing, engineering, economics, medicine and military. In recent years, there has been anincreasing interest in Game Artificial Intelligence or Game AI. Game AI refers to techniques applied incomputer and video games such as learning, pathfinding, planning, and many others for creating intelligentand autonomous behaviour to the characters in games. The main objective of this paper is to highlightseveral most common of the AI techniques for designing and controlling the computer-based charactersto play Ms. Pac-Man game between years 2005-2012. The Ms. Pac-Man is one of the games that used asbenchmark for comparison of autonomous controllers in a series of international Game AI competitions.An extensive content analysis method was conducted through critical review on previous literature relatedto the field. Findings highlight, although there was various and unique techniques available, the majorlimitation of previous studies for creating the Ms. Pac-Man game characters is a lack of generalizationcapability across different game characters. The findings could provide the future direction for researchersto improve the Generalization A.I capability of game characters in the Game Artificial Intelligence market.

A Review of Content Analysis on China Artificial Intelligence (AI) Education Policies

2021 ◽  
pp. 1-8
Author(s):  
Shaofang Wang ◽  
Guangming Wang ◽  
Xia Chen ◽  
Wei Wang ◽  
Xiaoming Ding
Keyword(s):  
Artificial Intelligence ◽  
Content Analysis ◽  
Education Policies

scholarly journals Managing Uncertainty in AI-Enabled Decision Making and Achieving Sustainability

2020 ◽  
Vol 12 (21) ◽  
pp. 8758
Author(s):  
Junyi Wu ◽  
Shari Shang
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Content Analysis ◽  
Literature Review ◽  
Uncertainty Management ◽  
Three Dimensions ◽  
Changing World

Artificial intelligence (AI) has been applied to various decision-making tasks. However, scholars have yet to comprehend how computers can integrate decision making with uncertainty management. Obtaining such comprehension would enable scholars to deliver sustainable AI decision-making applications that adapt to the changing world. This research examines uncertainties in AI-enabled decision-making applications and some approaches for managing various types of uncertainty. By referring to studies on uncertainty in decision making, this research describes three dimensions of uncertainty, namely informational, environmental and intentional. To understand how to manage uncertainty in AI-enabled decision-making applications, the authors conduct a literature review using content analysis with practical approaches. According to the analysis results, a mechanism related to those practical approaches is proposed for managing diverse types of uncertainty in AI-enabled decision making.

scholarly journals What Do Turkish Pre-Service Teachers Think About Artificial Intelligence?

2019 ◽  
Vol 3 (2) ◽  
pp. 3-23
Author(s):  
Halil Ibrahim Haseski
Keyword(s):  
Artificial Intelligence ◽  
Content Analysis ◽  
Structured Interview ◽  
Analysis Method ◽  
Negative Effects ◽  
Fall Semester ◽  
Future Studies ◽  
Content Analysis Method ◽  
Faculty Of Education ◽  
Academic Year

The aim of the present study was to determine the views of pre-service teachers on artificial intelligence. In the present qualitative study, conducted with the phenomenology design, that data were collected from 94 pre-service teachers attending different departments at Manisa Celal Bayar University, Faculty of Education during the 2018-2019 academic year fall semester in Turkey. Data were collected with semi-structured interview form and written interview form, developed by the author. Collected data were analyzed by using content analysis method and classified under themes. Analyses demonstrated that pre-service teachers assigned different meanings to artificial intelligence, felt basically negative emotions for artificial intelligence, and did not want to live in a world ruled by artificial intelligence. Furthermore, it was found that pre-service teachers considered that artificial intelligence could have both several benefits and risks, and it might have both positive and negative effects on education. Based on the study findings, various recommendations were presented for future studies and implementations on the topic.

scholarly journals Digitalization in the Labor Market in Russia

2021 ◽  
Vol 93 ◽  
pp. 01021
Author(s):  
Irina Omelchenko ◽  
Galina Antonova ◽  
Marina Danilina ◽  
Sergey Popkov ◽  
Ludmila Botasheva
Keyword(s):  
Artificial Intelligence ◽  
Content Analysis ◽  
Labor Market ◽  
Social Life ◽  
Business Processes ◽  
Information Communication ◽  
Economic Activities ◽  
Advanced Technologies ◽  
Modern Economy

In recent years the labor market experienced a number of changes. On the basis of the statistical and content analysis the authors research the main trends and indicators of the labor market. The modern economy and labor market are more and more clearly moving along the path of digitalization - the widespread introduction of the latest generation of advanced technologies (information, communication, robotics, artificial intelligence, etc.) into economic activities, completely changing the usual business processes. The pandemics of COVID19 has shown that the digitalization can be actively used in the companies and can change the situation in the labor market. Thus, digitalization affects all spheres of economic and social life, affects the demand for various categories ofworkers of various qualifications.

Literary Psychology-Modeling Figure-Ground Structures in Narrative Stories

2018 ◽  
pp. 205-240
Author(s):  
Eugene Schneider Kitamura
Keyword(s):  
Artificial Intelligence ◽  
Content Analysis ◽  
Autonomous Functioning ◽  
Narrative Context ◽  
Ground Structures ◽  
Content Generation

Today more than ever, narrative content generation has become important. This is due to the advances and accessibility of computational devices. As these devices become more familiar to people and easier to handle, there will be greater expectations for autonomous functioning and desires for a natural communication with the users. To achieve such demands, computational devices need to process and generate higher levels of meanings such as context and abstraction of topics. This chapter gives a background on topics that have been developed so far in content analysis and content generation, but focuses mainly on the figure-ground impression model, for both analysis and generating narrative context. By focusing on the characters and their attributes in the text, not only is this model able to represent the figure-ground impressions qualitatively, but also quantitatively. Such a feature may be useful to execute in computational devices such as artificial intelligence.

STATE POLICY OF ARTIFICIAL INTELLIGENCE DEVELOPMENT IN RUSSIA: AN ANALYSIS OF STRATEGIC GOALS

2020 ◽  
Vol 26 (8) ◽  
pp. 69-76
Author(s):  
V. Blanutsa ◽  
Keyword(s):  
Artificial Intelligence ◽  
Content Analysis ◽  
State Policy ◽  
Time Lag ◽  
National Strategy ◽  
General Intelligence ◽  
Artificial General Intelligence ◽  
Strategic Goals ◽  
The Creation ◽  
Intelligence Development

The state policy of artificial intelligence development in Russia is based on the national strategy approved in 2019 and valid until 2030. To understand the specifics of Russian policy, a national strategy was chosen as the object of research, and the subject of research was declared and latent strategic goals. The study is aimed at assessing the degree of correspondence between the strategic goals of state policy and modern concepts of artificial intelligence development. For the automatic analysis of the texts of the national strategy, similar foreign documents and the global array of publications, content analysis was used. The eight largest bibliographic databases have identified many original scientific articles on artificial intelligence. Content analysis of this array made it possible to identify six approaches (algorithmic, test, cognitive, landscape, explanatory and heuristic) to the construction of a concept for the development of artificial intelligence. The latter approach is the most end-to-end, allowing generalizing the rest of the approaches. Further analysis was carried out on the basis of a heuristic approach, within which the concepts of narrow, general and super intelligence are highlighted. The text of the national strategy was analyzed for compliance with the three concepts. It was found that the goals announced in the national strategy refer to the concept of artificial narrow intelligence. Analysis of the frequency of occurrence of terms in the strategy revealed latent goals (access to big data and software) that belong to the same concept. The study of the context of several cases of mentioning artificial general intelligence in the strategy only confirmed the general focus on the development of artificial narrow intelligence. The leading countries in the analyzed area are characterized by a strategic focus on the development of technologies for artificial general intelligence and scientific research on artificial superintelligence. The approximate time lag of the Russian strategy from the creation of artificial general intelligence has been determined. To overcome this lag and Russia occupy a leading position in the world, it was proposed to develop a new national strategy for the creation of artificial superintelligence technologies in the period up to 2050

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