• Title/Summary/Keyword: behavior-based AI

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Research on Influencing Factors of Purchasing Behavior of AI Speakers in China based on the UTAUT and TTF Model

  • Wenyan Chang;Jung Mann Lee
    • Journal of Information Technology Applications and Management
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    • v.29 no.5
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    • pp.13-25
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    • 2022
  • The purpose of this study is to explore the factors that influence the purchase of AI speakers in China. We integrate the Unified Theory of Acceptance and Use of Technology (UTAUT) and Task-technology fit (TTF) model into one model and put forward assumptions. According to the characteristics of AI speakers, we selected 6 independent variables, such as Performance Expectation, Effort Expectation, Social Influence, Facilitating Conditions, Task and Technology-characteristics. The final impact on purchase behavior is evaluated through Task-technology fit and purchase intention. After counting 478 samples, through SPSS22.0 and AMOS analysis, hypotheses have been proved by strong experimental data, except facilitating conditions. These results also imply that improving the technical level of AI speakers and enhancing consumers' purchasing intention are the central line of marketing. Based on this, we put forward several suggestions to marketers, including strengthening the research and development of AI speaker technology, and building a circle of friends of AI speakers.

A Comparative Study on Behavior-based Agent Control for Computer Games

  • Kim, Tae-Hee
    • Journal of Korea Game Society
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    • v.2 no.2
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    • pp.37-45
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    • 2002
  • Computer games could be regarded as simulation of the real world. Control problems of software agents have long been studied in the field of Artificial Intelligence (AI), resulting in giving a birth to the behavior-based approach. three main approaches might be categorized out of the history of AI study. First, Cognitivists propose that intelligence could be represented and manipulated in terms of symbols. Second, Connectionists claim that symbols could not be isolated but they are embedded in the body structure. Third, the behavior-based approach is an approach to AI which suggests that intelligence is dynamic property that exists nowhere but emerges in the relationship of an agent and the world including observers while the agent performs behavior. This paper explains and compares the three approaches to AI, then discusses the plausibility of the behavior-based approach and problems. Finally, this paper proposes application of behavior-based approach to computer games in terms of agent control.

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An Efficiency Analysis of an Artificial Intelligence Medical Image Analysis Software System : Focusing on the Time Behavior of ISO/IEC 25023 Software Quality Requirements (인공지능 기술 기반의 의료영상 판독 보조 시스템의 효율성 분석 : ISO/IEC 25023 소프트웨어 품질 요구사항의 Time Behavior를 중심으로)

  • Chang-Hwa Han;Young-Hwang Jeon;Jae-Bok Han;Jong-Nam Song
    • Journal of the Korean Society of Radiology
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    • v.17 no.6
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    • pp.939-945
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    • 2023
  • This study analyzes the 'performance efficiency' of AI-based reading assistance systems in the field of radiology by measuring their 'time behavior' properties. Due to the increase in medical images and the limited number of radiologists, the adoption of AI-based solutions is escalating, stimulating a multitude of studies in this area. Contrary to the majority of past research which centered on AI's diagnostic precision, this study underlines the significance of time behavior. Using 50 chest X-ray PA images, the system processed images in an average of 15.24 seconds, demonstrating high consistency and reliability, which is on par with leading global AI platforms, suggesting the potential for significant improvements in radiology workflow efficiency. We expect AI technology to play a large role in the field of radiology and help improve overall healthcare quality and efficiency.

Future Trends of AI-Based Smart Systems and Services: Challenges, Opportunities, and Solutions

  • Lee, Daewon;Park, Jong Hyuk
    • Journal of Information Processing Systems
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    • v.15 no.4
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    • pp.717-723
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    • 2019
  • Smart systems and services aim to facilitate growing urban populations and their prospects of virtual-real social behaviors, gig economies, factory automation, knowledge-based workforce, integrated societies, modern living, among many more. To satisfy these objectives, smart systems and services must comprises of a complex set of features such as security, ease of use and user friendliness, manageability, scalability, adaptivity, intelligent behavior, and personalization. Recently, artificial intelligence (AI) is realized as a data-driven technology to provide an efficient knowledge representation, semantic modeling, and can support a cognitive behavior aspect of the system. In this paper, an integration of AI with the smart systems and services is presented to mitigate the existing challenges. Several novel researches work in terms of frameworks, architectures, paradigms, and algorithms are discussed to provide possible solutions against the existing challenges in the AI-based smart systems and services. Such novel research works involve efficient shape image retrieval, speech signal processing, dynamic thermal rating, advanced persistent threat tactics, user authentication, and so on.

Game AI Agents using Deliberative Behavior Tree based on Utility Theory (효용이론 기반 숙고형 행동트리를 이용한 게임 인공지능 에이전트)

  • Kwon, Minji;Seo, Jinsek
    • Journal of Korea Multimedia Society
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    • v.25 no.2
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    • pp.432-439
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    • 2022
  • This paper introduces deliberative behavior tree using utility theory. The proposed approach combine the strengths of behavior trees and utility theory to implement complex behavior of AI agents in an easier and more concise way. To achieve this goal, we devised and implemented three types of additional behavior tree nodes, which evaluate utility values of its own node or its subtree while traversing and selecting its child nodes based on the evaluated values. In order to validate our approach, we implemented a sample scenario using conventional behavior tree and our proposed deliberative tree respectively. And then we compared and analyzed the simulation results.

Application of Artificial Intelligence for the Management of Oral Diseases

  • Lee, Yeon-Hee
    • Journal of Oral Medicine and Pain
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    • v.47 no.2
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    • pp.107-108
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    • 2022
  • Artificial intelligence (AI) refers to the use of machines to mimic intelligent human behavior. It involves interactions with humans in clinical settings, and augmented intelligence is considered as a cognitive extension of AI. The importance of AI in healthcare and medicine has been emphasized in recent studies. Machine learning models, such as genetic algorithms, artificial neural networks (ANNs), and fuzzy logic, can learn and examine data to execute various functions. Among them, ANN is the most popular model for diagnosis based on image data. AI is rapidly becoming an adjunct to healthcare professionals and is expected to be human-independent in the near future. The introduction of AI to the diagnosis and treatment of oral diseases worldwide remains in the preliminary stage. AI-based or assisted diagnosis and decision-making will increase the accuracy of the diagnosis and render treatment more precise and personalized. Therefore, dental professionals must actively initiate and lead the development of AI, even if they are unfamiliar with it.

Design of an IMU-based Wearable System for Attack Behavior Recognition and Intervention (공격 행동 인식 및 중재를 위한 IMU 기반 웨어러블 시스템 개발)

  • Woosoon Jung;Kyuman Jeong;Jeong Tak Ryu;Kyoung-Ock Park;Yoosoo Oh
    • Smart Media Journal
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    • v.13 no.5
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    • pp.19-25
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    • 2024
  • The biggest type of behavior that prevents people with developmental disabilities from entering society is aggressive behavior. Aggressive behavior can pose a threat not only to the personal safety of the person with a developmental disability, but also to the physical safety of others. In this study, we propose a wearable system using a low-power processor. The proposed system uses an IMU (Inertial Measurement Unit) to analyze user behavior, and when attack behavior is not detected for a certain period of time through an LED array attached to the developed system, an interesting LED is displayed. By expressing patterns, we provide behavioral intervention through compensation to people with developmental disabilities. In order to implement a system that must be worn for a long time in a power-limited environment, we present a method to optimize performance and energy consumption across all stages, from data preprocessing to AI model application.

Artificial Intelligence Based Medical Imaging: An Overview (AI 의료영상 분석의 개요 및 연구 현황에 대한 고찰)

  • Hong, Jun-Yong;Park, Sang Hyun;Jung, Young-Jin
    • Journal of radiological science and technology
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    • v.43 no.3
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    • pp.195-208
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    • 2020
  • Artificial intelligence(AI) is a field of computer science that is defined as allowing computers to imitate human intellectual behavior, even though AI's performance is to imitate humans. It is grafted across software-based fields with the advantages of high accuracy and speed of processing that surpasses humans. Indeed, the AI based technology has become a key technology in the medical field that will lead the development of medical image analysis. Therefore, this article introduces and discusses the concept of deep learning-based medical imaging analysis using the principle of algorithms for convolutional neural network(CNN) and back propagation. The research cases application of the AI based medical imaging analysis is used to classify the various disease(such as chest disease, coronary artery disease, and cerebrovascular disease), and the performance estimation comparing between AI based medical imaging classifier and human experts.

Trends in the AI-based Banking Conversational Agents Literature: A Bibliometric Review

  • Eden Samuel Parthiban;Mohd. Adil
    • Asia pacific journal of information systems
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    • v.33 no.3
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    • pp.702-736
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    • 2023
  • Artificial Intelligence (AI) and the technologies powered by AI fuel the fourth industrial revolution. Being the primary adopter of such innovations, banking has recently started using the most common AI-based technology, i.e., conversational agents. Although research extensively focuses on this niche area and provides bibliometric understanding for such agents in other industries, a similar review with scientometric insights of the banking literature concerning AI conversational agents is absent till date. Furthermore, in the era following the pandemic, banks are faced with the imperative to provide solutions that align with the changing landscape of remote consumer behavior. As a result, banks are proactively integrating technology-driven solutions, such as automated agents, to effectively address the growing demand for remote customer support. Hence more research is needed to perfect such agents. In order to bridge these existing gaps, the present study undertook a comprehensive examination of two decades' worth of banking literature. A meticulous review was conducted, analyzing approximately 116 papers published from 2003 to 2023. The aim was to provide a scientometric overview of the topic, catering to the research needs of both academic and industrial professionals. Holistically, the study seeks to present a macro-view about the existing trends in AI based banking conversational agents' literature while focusing on quantity, qualitative and structural indicators that are effectively necessary to offer new directions for the AI-based banking solutions. Our study, therefore, presents insights surrounding the literature, using selected techniques related to performance analysis and science mapping.

The Development of Rule-based AI Engagement Model for Air-to-Air Combat Simulation (공대공 전투 모의를 위한 규칙기반 AI 교전 모델 개발)

  • Minseok, Lee;Jihyun, Oh;Cheonyoung, Kim;Jungho, Bae;Yongduk, Kim;Cheolkyu, Jee
    • Journal of the Korea Institute of Military Science and Technology
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    • v.25 no.6
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    • pp.637-647
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    • 2022
  • Since the concept of Manned-UnManned Teaming(MUM-T) and Unmanned Aircraft System(UAS) can efficiently respond to rapidly changing battle space, many studies are being conducted as key components of the mosaic warfare environment. In this paper, we propose a rule-based AI engagement model based on Basic Fighter Maneuver(BFM) capable of Within-Visual-Range(WVR) air-to-air combat and a simulation environment in which human pilots can participate. In order to develop a rule-based AI engagement model that can pilot a fighter with a 6-DOF dynamics model, tactical manuals and human pilot experience were configured as knowledge specifications and modeled as a behavior tree structure. Based on this, we improved the shortcomings of existing air combat models. The proposed model not only showed a 100 % winning rate in engagement with human pilots, but also visualized decision-making processes such as tactical situations and maneuvering behaviors in real time. We expect that the results of this research will serve as a basis for development of various AI-based engagement models and simulators for human pilot training and embedded software test platform for fighter.