Selected Technology Thrusts Supporting Emerging Training Systems: Computer-Based Authoring, Artificial Intelligence, and Embedded Training

1986 ◽  
Vol 30 (6) ◽  
pp. 595-598
Author(s):  
J. Peter Kincaid
Keyword(s):  
Artificial Intelligence ◽  
Research And Development ◽  
Military Training ◽  
Technical Information ◽  
Research Issues ◽  
Weapon Systems ◽  
Future Design ◽  
Training Systems ◽  
Computer Based ◽  
Limited Degree

This symposium is a follow-up to a sumposium held at last year's HFS meeting. “Training Technology in the 1990s: Development, Application and Research Issues.” Representatives from the three military services discussed how many facets of training technology would affect current and future design applications and research issues relevant to military training systems. Two topics from that session (artificial intelligence and embedded training) and one other topic (computer-based authoring of technical information) have beer selected for in-depth discussion. Each technology is computer-based and has been exploited to only a limited degree. The object of this symposium is to provide a focus for describing how the three technologies are important for emerging and future training systems. For example, nearly all technical information (TI) for maintaining and operating weapon systems in the field is currently paper-based but the Department of Defense is committed to transitioning to electronic delivery of TI within the next decade. Many R&D issues must be resolved in the interim. Similarly, the technologies of embedded training and artificial intelligence have considerable potential for future training systems once a number of R&D issues are successfully addressed. All three services have on-going research and development programs for the technologies covered in this sumposium. Each topic is presented by representatives from at least two military behavioral laboratories: for computer-based authoring, Naval Training Systems Center (NTSC), Naval Personnel Research and Development Center (NPRDC) and Army Research Institute (ARI); for artificial intelligence, Air Force Human Resources Laboratory (AFHRL) and NTSC; and for embedded training, NTSC and ARI. The goals of the symposium are: (1) to make clearer the most pressing R&D issues associated with these technologies, and (2) to discuss how future training systems might incorporate them.

Evaluating the Impact of Automated Technology in Basic Military Training Using Computer-Based Surveys

1997 ◽  
Author(s):  
Walter G. Albert ◽  
Winston Bennett ◽  
Kenneth Pemberton ◽  
Charles Holt ◽  
Pat Waldroop
Keyword(s):  
Military Training ◽  
Automated Technology ◽  
Computer Based ◽  
The Impact

scholarly journals Peacekeeping Conditions for an Artificial Intelligence Society

2019 ◽  
Vol 3 (2) ◽  
pp. 34
Author(s):  
Hiroshi Yamakawa
Keyword(s):  
Artificial Intelligence ◽  
Intelligent Agents ◽  
Human Society ◽  
Common Value ◽  
Goal Management ◽  
Computer Based ◽  
Common Goals ◽  
Near Future ◽  
Advanced System ◽  
Local Value

In a human society with emergent technology, the destructive actions of some pose a danger to the survival of all of humankind, increasing the need to maintain peace by overcoming universal conflicts. However, human society has not yet achieved complete global peacekeeping. Fortunately, a new possibility for peacekeeping among human societies using the appropriate interventions of an advanced system will be available in the near future. To achieve this goal, an artificial intelligence (AI) system must operate continuously and stably (condition 1) and have an intervention method for maintaining peace among human societies based on a common value (condition 2). However, as a premise, it is necessary to have a minimum common value upon which all of human society can agree (condition 3). In this study, an AI system to achieve condition 1 was investigated. This system was designed as a group of distributed intelligent agents (IAs) to ensure robust and rapid operation. Even if common goals are shared among all IAs, each autonomous IA acts on each local value to adapt quickly to each environment that it faces. Thus, conflicts between IAs are inevitable, and this situation sometimes interferes with the achievement of commonly shared goals. Even so, they can maintain peace within their own societies if all the dispersed IAs think that all other IAs aim for socially acceptable goals. However, communication channel problems, comprehension problems, and computational complexity problems are barriers to realization. This problem can be overcome by introducing an appropriate goal-management system in the case of computer-based IAs. Then, an IA society could achieve its goals peacefully, efficiently, and consistently. Therefore, condition 1 will be achievable. In contrast, humans are restricted by their biological nature and tend to interact with others similar to themselves, so the eradication of conflicts is more difficult.

Seven Things Every Trainer Must Know about Artificial Intelligence

1991 ◽  
Vol 20 (2) ◽  
pp. 153-156
Author(s):  
Mahima Ranjan Kundu
Keyword(s):  
Artificial Intelligence ◽  
Expert Systems ◽  
Business Management ◽  
Human Mind ◽  
Educational Programs ◽  
Training Environment ◽  
Training And Education ◽  
Training Systems ◽  
Potential Benefits

This article provides information about the prospects and limitations of the Artificial Intelligence and Expert Systems as they relate to training systems and educational programs. The article describes the potential benefits of expert systems and how it can be gainfully employed in training environment, industry, and business management to perform complex jobs. The limitations of the applications of the Artificial Intelligence are discussed as some tend to believe that human mind and computers think alike and AI machines can function like a real expert in every aspect of training and education.

Feature-Based Design: 4 Hypotheses for Future CAD Systems

1993 ◽  
Author(s):  
David W. Rosen
Keyword(s):  
Future Research ◽  
Design Activity ◽  
Research Directions ◽  
Research Issues ◽  
Cad Systems ◽  
Feature Representations ◽  
Feature Based ◽  
Computer Based ◽  
Definition Of ◽  
Feature Based Design

Abstract Features are meaningful abstractions of geometry that engineers use to reason about components, products, and processes. For design activity, features are design primitives, serve as the basis for product representations, and can incorporate information relevant to life-cycle activities such as manufacturing. Research on feature-based design has matured to the point that results are being incorporated into commercial CAD systems. The intent here is to classify feature-based design literature to provide a solid historical basis for present research and to identify promising research directions that will affect computer-based design tools within the next few years. Applications of feature-based design and technologies of feature representations are reviewed. Open research issues are identified and put in the context of past and current work. Four hypotheses are proposed as challenges for future research: two on the existence of fundamental sub-feature elements and relationships for features, one that presents a new definition of design features, and one that argues for the successful development of concurrent engineering languages. Evidence for these hypotheses is provided from recent research results and from speculation about the future of feature-based design.

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.

Frontier: Autonomy in Detection, Actuation, and Planning for Robotic Weeding Systems

2021 ◽  
Vol 64 (2) ◽  
pp. 557-563
Author(s):  
Piyush Pandey ◽  
Hemanth Narayan Dakshinamurthy ◽  
Sierra N. Young
Keyword(s):  
Artificial Intelligence ◽  
Deep Learning ◽  
Research And Development ◽  
Weed Control ◽  
List Type ◽  
Automated Systems ◽  
Weed Detection ◽  
Detection And Identification ◽  
Key Technologies ◽  
Robotic Weeding

HighlightsRecent research and development efforts center around developing smaller, portable robotic weeding systems.Deep learning methods have resulted in accurate, fast, and robust weed detection and identification.Additional key technologies under development include precision actuation and multi-vehicle planning. Keywords: Artificial intelligence, Automated systems, Automated weeding, Weed control.

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