• The KIPS Transactions:PartB
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• v.10B no.7
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• pp.795-802
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• 2003

To live autonomously, intelligent agents such as robots or virtual characters need ability that recognizes given environment, and learns and chooses adaptive actions. So, we propose an action selection/learning mechanism in intelligent agents. The proposed mechanism employs a hybrid system which integrates a behavior-based method using the reinforcement learning and a cognitive-based method using the symbolic learning. The characteristics of our mechanism are as follows. First, because it learns adaptive actions about environment using reinforcement learning, our agents have flexibility about environmental changes. Second, because it learns environmental factors for the agent's goals using inductive machine learning and association rules, the agent learns and selects appropriate actions faster in given surrounding and more efficiently in extended surroundings. Third, in implementing the intelligent agents, we considers only the recognized states which are found by a state detector rather than by all states. Because this method consider only necessary states, we can reduce the space of memory. And because it represents and processes new states dynamically, we can cope with the change of environment spontaneously.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07a
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• pp.535-537
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• 2005

본 논문에서는 스마트 센서 네트워크에서 컨텍스트 인지 서비스를 제공하는 미들웨어를 제안한다. 미들웨어는 UPnP를 이 용하여 어플리케이션과 스마트 센서 네트워크가 플러그 앤 플레이로 서비스의 상호운용을 제공하며, 컨텍스트 인지 서비스 에이전트를 통해 XML 기반의 서비스 명세가 개별 센서 네트워크에서 자동으로 실행 될 수 있는 코드를 생성한다. 이상의 미들웨어를 이용하여 개발자는 UPnP나 스마트 센서 네트워크에 대한 고려 없이 XML을 이용한 간단한 서비스 명세만으로 손쉽게 컨텍스트 인지 서비스를 지원하는 어플리케이션을 개발 할 수 있다.

• Journal of Intelligence and Information Systems
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• v.11 no.3
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• pp.129-139
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• 2005

The rapid growth of IT technologies enables the quality of human's daily life to be improved dramatically, Contrasting to the services in previous computing environment directed by user's request, the services in ubiquitous computing era of new IT technology are provided through recognizing users intention and utilizing context-aware information suited to the user. According to the contextual information, agents need to set a dynamic goal to achieve and work collaboratively with other agents. Agents that take control over their behaviors with capability of communicating with other agents become a thrust in this up-coming computing environment. This work focuses on building ontologies, shared knowledge bases among agents, to improve semantical interoperability among agents. More attention is given to the construction and effective management of ontology repository along with its requirement and organization. Ontology agent suggested takes an initiative role to manage the repository in a distributed manner and to facilitate the use of ontology in a multi-agent environment.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.05a
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• pp.383-384
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• 2010

• 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.

• Science of Emotion and Sensibility
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• v.15 no.1
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• pp.47-56
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• 2012

The purpose of this study is to test the effect of pedagogical agent realism and expertise on persona effect. There were two perspectives of the pedagogical agents' social interaction. Self-identification hypothesis argues that complexity of agent image is better to increase social interaction. Subjective identification insists that simplified image is more helpful to facilitate social interaction. However, from the cognitive load theory perspective, learners' expertise can be a major factor to determine persona effect. Sixty-eight college students (male=19 and female=49) participated. The independent variables were the degree of realism of pedagogical agent (detailed vs. simplified image) and the expertise (high prior knowledge group vs. low prior knowledge group). The dependant variables were comprehension test and the agent persona instrument (API). There was no significant difference in comprehension test score; however, there were significant interaction effect on the most constructs of API: 1) facilitating of learning, 2) credible, and 3) human-like. The follow-up analysis of simple main effect revealed that high expertise group showed significantly higher perception of the three construct with high realism of pedagogical agent. The results of study show that learners' expertise plays a key role of perception of persona effect.

• Korean Journal of Cognitive Science
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• v.10 no.1
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• pp.67-78
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• 1999

Information providers on WWW have been rapidly increasing, and they provide a vast amount of information in various fields, Because of this reason, it becomes hard for users to get the information they want. Although there are several search engines that help users with the keyword matching methods, it is not easy to find suitable keywords. In order to solve these problems with a specific domain, we propose an intelligent information agent(HHA-la : HongIk Information Agent) that converts user's q queries to forms including related domain words in order to represent user's intention as much as it can and provides the necessary information of the domain to users. HHA-la h has an ontological knowledge base of animal domain, supplies necessary information for queries from users and other agents, and provides relevant web page information. One of system components is a WebDB which indexes web pages relevant to the animal domain. The system also supplies new operators by which users can represent their thought more clearly, and has a learning mechanism using accumulated results and user feedback to behave more intelligently, We implement the system and show the effectiveness of the information agent by presenting experiment results in this paper.

• Korean Journal of Cognitive Science
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• v.13 no.4
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• pp.1-8
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• 2002

As Internet grows, many web sites have been built, therefore much information has been registered. Because the web sites have more information, it is more difficult that the user can find the information wanted. Therefore, to get information that user wants easily, the full-text engine may be embedded to the web site. This paper is about developing the help conversational agent for a user to find the information that he wants through conversation with agent. The proposed method is based on the pattern matching of artificial intelligence, not natural language processing. If a user inputs any sentence, the help conversational agent responds to the sentence through preprocessing and pattern matching with knowledge. The knowledge is built with the XML format. With the approximate pattern matching, the agent picks up the appropriate response with some degree of similarities. At the experiment, some different sentences with the same meaning have been entered, then the agent recognized them as the same pattern, and it made a correct answer.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.168-173
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• 2008

Recently, many researchers have studied on agent-based edutainment systems to improve students' learning experience. In this paper, we present AR Gardening which makes users experience interactive flower gardening with a bluebird, a learning companion agent, squatting in an augmented picture. The proposed system augments the animated bluebird to support interactive edutainment experiences. The bluebird perceives users' actions as well as environmental situations. It then appraises situational information to provide participants with problem-solving guidelines. Moreover, the bluebird responds like a companion than an instructor through anthropomorphic expression. To demonstrate our work, we exhibited the implemented AR Gardening and reviewed participants' responses to the system. In this exhibition, we could find that the learning companion-like bluebird helped users experience how to properly grow the flower in our educational setting. Ultimately, we expect that an augmented peer learning agent is one of the key factors for developing effective edutainment applications.

• 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.