• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2019.05a
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• pp.8-9
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• 2019

해상교통과 같이 선박, 항해자, 관제센터, 해운선사, 기상시스템, 지리정보시스템 등의 높은 복잡도와 방대한 범위의 요구사항을 갖는 시스템의 M&S를 위해서는 인간을 포함한 체계가 필요하다. 디지털 환경에서 해상교통을 모의하기 위해서는 주요 요소인 인적요인에 대한 모델링 필요하며, 현실감 있는 해상교통 상황의 재현 및 예측을 위해 항해자의 인지과정, 행동양식, 항해전문성, 항해오류 등을 모델링하여 반영하는 것이 타당하다. 본 발표에서는 해상교통류 분석을 위한 지능형 선박 에이전트 개발을 위해 선박운항과 관련된 항해자의 인지 및 행동을 분석하고, 이를 통해 분석된 정보를 이용하여 항해자의 행동과 유사한 에이전트 기반의 인지 및 행동 모델 개발 내용을 소개하고자 한다.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.3
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• pp.51-58
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• 2010

Since Augmented Reality (AR) enables users to experience computer-generated content embedded in real environments, AR agents can be visualized among physical objects in the environments where the users exist, and directly interact with them in real-time. We model perceptual attention for autonomous agents in AR environments where virtual and physical objects coexist. Since such AR agents must adaptively perceive and attend to surrounded objects relevant to their goals, our model allows the agents to determine currently visible objects from the description of what virtual and physical objects are configured in the camera's viewing area. A degree of attention is assigned to each perceived object based on its relevance to achieve agents' goals. The agents can focus on a reduced set of perceived objects with respect to the estimated degree of attention. To demonstrate the effectiveness of our approach, we implemented an animated character that was overlaid over a miniature version of campus and that attended to buildings relevant to their goals. Experiments showed that our model could reduce the character's perceptual loads even when surroundings change.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2020.11a
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• pp.179-180
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• 2020

해상교통을 모의하기 위해서는 주요 요소인 선박운항자의 인적요인에 대한 모델링 필요하며, 현실감 있는 해상교통 상황의 재현 및 예측을 위해 선박운항자 행동양식, 항해전문성, 항해오류 등을 모델링하여 반영하는 것이 필요하다. 본 발표에서는 에이전트 기반의 해상교통 시뮬레이션을 위해서 선박운항자의 충동회피를 위한 행동 분석를 수행했으며, 기초 데이터의 확보를 위해 설문조사를 실시하였다. 설문조사를 통해 분석된 정보를 이용하여 선박 충돌상황에서 선박운항자의 행동과 유사한 에이전트 기반의 항해행동 모델 개발현황을 소개하고자 한다.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.4
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• pp.1-10
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• 2010

This present paper's goal is to show a virtual human agent's movement-data loci based on realistically limited perception data is human-like. To determine human-likeness of the movement-data loci, we consider interactions between two parameters: Realistically Limited Perception (RLP) data and Incremental Movement-Path data Generation (IMPG). That is to consider how the former (i.e., RLP), one of the simulated parameters of human thought or its elements dictates the latter (i.e., IMPG), one of the simulated parameters of human movement behavior. Mapping DB is a prerequisite for navigation in an agent system because it functions as an interface between perception and movement behavior. Although Hill et al. studied mapping DB methodology based on RLP, their research dealt only with a rendering camera's view point data. The agent system in this present paper was integrated with the Hill's mapping DB module and then the two parameters' interaction was considered on a military reconnaissance mission with unexpected enemy emergence. Movement loci that were generated by the agent and subjects were compared with each other. The agent system in this present research verifies that it can be a functional test bed for producing human-like movement-data loci although the human-likeness of agent is the result of a pilot test, determined by two parameters (RLP and IMPG) and only 30 subjects.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.5
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• pp.63-73
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• 2008

Recent years have seen an explosion of interest in interactive agents motivating human learners to engage in edutainment systems which are designed to be entertaining and educational at the same time. Especially, work on socio-emotional processes has focus on understanding of human's social behavior in training and entertainment a applications. In contrast with work on social emotion, where research groups have developed detailed models of emotional processes, models of personality have emphasized shallow surface behavior. Here, we build on computational appraisal models of emotion to better characterize dispositional differences in how people come to understand social situations. Known as explanatory style, this dispositional factor plays a key role in social interactions and certain socio-emotional disorders, such as depression. Building on appraisal and attribution theories, we model key conceptual variables underlying the explanatory style, and enable agents to exhibit different explanatory tendencies with respect to their personalities. Furthermore, we developed an interactive AR agent based on our framework and applied it into an interactive teaming system that allows participants to explore individual differences in the explanation of social events, with the goal of encouraging the development of perspective laking and emotion-regulatory skills.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10a
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• pp.88-90
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• 2004

유비쿼터스 환경에서 에이전트는 사용자와 시스템의 인터페이스 역할을 한다. 본 논문에서는 현재 상황을 인지하여 사용자의 행위에 따른 서비스를 제공하는 연구를 수행하였다. 본 논문에서 사용하는 서비스 추론 방법은 온톨로지를 기반으로 정의한 도메인에 대한 규칙을 사용한다. 온톨로지는 다양한 환경에서 도메인의 지식(knowledge)을 공유하고 재 사용할 수 있기 때문에 현재 상황에 맞는 서비스를 추론할 수 있다. 또한 본 논문에서는 에이전트의 역할을 나누고 에이전트간의 커뮤니케이션을 통해 추론된 서비스를 환경에 반영한다. 이처럼 온톨로지를 이용하여 환경을 모델링 하고 규칙을 기반으로 서비스를 추론함으로, 같은 상황이더라도 사용자에 따라 추론되어지는 서비스가 달라진다. 즉, 주어진 상황뿐 아니라 사용자에 따라 제공되는 서비스가 달라지도록 사용자 중심의 서비스 예측의 정확성을 높이도록 연구하였다.

• The KIPS Transactions:PartB
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• v.8B no.5
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• pp.485-492
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• 2001

Recently, character agents are used as a user-friendly interface. In this paper, we have studied a generic framework for emotional character agents which are designed to infer emotions from diverse personalities, situations, user behaviors and to express them. The method of emotion inference is based on blackboard systems which are used to solve the problems in AI. Because it keeps independence between knowledge sources which are rules of emotions, a blackboard-based inference engine is easy to manage knowledge sources, Blackboard-based systems gave the system flexibility. So we can adapt the engine to various application systems. Each emotional agent monitors user behavior, learns user profile and infers user behavior. And it generates characters emotions according to the user profile. So, in case of same situations, the agent can generate different emotions according to users. We have studied to build an personalized emotional character agent which according to situations and user modeling.

• Journal of Navigation and Port Research
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• v.44 no.6
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• pp.469-476
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• 2020

Modeling and Simulation (M&S) systems which deal with situational complexity often require human involvement due to the high-level decision-making that is necessary for ship movement, navigation, control center management, shipping company logistics, meteorological system information, and maritime transportation GIS. In order to properly simulate maritime traffic, it is necessary to accurately model the human decision-making process of the ship officer, including aspects of the ship officer's behavioral tendencies, personal navigation experience, and pattern of voyage errors, as this is the most accurate way in which to reproduce and predict realistic maritime traffic conditions. In this paper, which looks at agent-based maritime traffic simulation, we created a basic survey in order to conduct behavior analysis on ship operators' collision avoidance strategies. Using the information gathered throughout the survey, we developed an agent-based navigational behavior model which attempts to capture the behavioral patterns of a ship officer during an instance of ship collision. These results could be used in the future in further developments for more advanced maritime traffic simulation.

• Science of Emotion and Sensibility
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• v.13 no.3
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• pp.429-440
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• 2010

It is known that as many as 1 in 91 children are diagnosed with an autistic spectrum disorder, and the incidence rate of the autistic spectrum disorder is much higher than that of cancer in Korea. It is necessary to develop a novel technology to sense their emotional status and give proper psychological diagnosis and therapy, since the children with autistic spectrum disorder usually do not express their own emotional status. This article presents the state-of-the-arts on the affective computing technologies that include recognition of emotional status through bio-sensing and virtual affective agent modeling, and then proposes a novel system architecture for diagnosis and therapy of autistic spectrum disorder. The diagnosis and therapy system of autistic spectrum disorder is composed of bio-sensing module, virtual environment module with affective agents, and haptic interface module. The architecture proposed in this paper will enhance the objectivity to diagnose autism spectrum disorders, and enable continuous treatment in daily life.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.8
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• pp.299-308
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• 2014

Various literatures related computing of information processing have been recently shown the researches inspired from the remarkably excellent human capabilities which recognize and categorize very complex visual patterns such as body motions and facial expressions. Applied from human's outstanding ability of perception, the classification function of visual sequences without context information is specially crucial task for computer vision to understand both the coding and the retrieval of spatio-temporal patterns. This paper presents a biological process based action recognition model of computer vision, which is inspired from visual information processing of human brain for action recognition of visual sequences. Proposed model employs the structure of neural fields of bio-inspired visual perception on detecting motion sequences and discriminating visual patterns in human brain. Experimental results show that proposed recognition model takes not only into account several biological properties of visual information processing, but also is tolerant of time-warping. Furthermore, the model allows robust temporal evolution of classification compared to researches of action recognition. Presented model contributes to implement bio-inspired visual processing system such as intelligent robot agent, etc.