• Korean Journal of Cognitive Science
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• v.14 no.3
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• pp.13-21
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• 2003

This study presents a design of Teachable Agent(TA) and its theoretical background. TA is an intelligent agent to which students as tutors teach, pose questions, and provide feedbacks using a concept map. TA consists of four independent Modules, Teach Module, Q&A Module, Test Module, and Resource Module. In Teach Module, students teach TA by constructing concept map. In Q&A Module, both students and TA ask questions and answer questions each other through an interactive window. To assess TA's knowledge and provide feedback to students, Test Module consists of a set of predetermined questions which TA should pass. From Resource Module, students can search and look up important information to teach, ask questions, and provide feedbacks whenever they want. It is expected that TA should provide student tutors with an active role in learning and positive attitude toward the subject matter by enhancing their cognition as well as motivation.

• 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.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.16-22
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• 2001

There is no doubt that agents play an increasingly predominant role in e-commerce, whether these are business-to-consumer or business-to-business applications. However most of the current e-commerce agents only support a single bid for a product at a fixed price. Although price is an important factor, it is not the only concern of both business and consumer. There is doubt as to whether such agents satisfv both parties. Negotiation on a variety of issues is needed in order to reach an agreement. In this paper, a computational agent negotiation(CAN) model is proposed to facilitate multiple-issue negotiation via an agent. The main contribution of the CAN model is it enables agent to participate actively in the negotiation with various feedback instead of simply an agreement or rejection.

• Journal of the Korean Society for Precision Engineering
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• v.32 no.1
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• pp.39-47
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• 2015

Globalization, unpredictable markets, increased products customization and frequent changes in products, production technologies and machining systems have become a complexity in today's manufacturing environment. One key strategy for coping with the evolution of this situation is to develop or apply an enable technology such as intelligent manufacturing. Intelligent manufacturing system (IMS) is characterized by decentralized, distributed, networked compositions of heterogeneous and autonomous systems. The model of IMS is inherited from the organization of the living systems in biology and nature so that the manufacturing system has the advanced characteristics inspired from biology such as self-adaptation, self-diagnosis, and selfhealing. To prove this concept, an innovative system with applying the advanced information and communication technology such as internet of things, cognitive agent are proposed to integrate, organize and allocate the machining resources. Innovative system is essential for modern machining system to flexibly and quickly adapt to new challenges of manufacturing environment.

• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.945-953
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• 2006

The researchers in the field of cognitive science and learning science suggest that the teaching activity induces the elaborative and meaningful learning. Actually, lots of research findings have shown the beneficial effect of learning by teaching such as peer tutoring. But peer tutoring has some limitations in the practical learning context. To overcome some limitations, the new concept of "learning by teaching" through the agent called Teachable Agent. The teachable agent is a modified version of traditional intelligent tutoring system that assigns a role of tutor to teach the agent. The teachable agent monitors individual difference and provides a student with a chance for deep learning and motivation to learn by allowing them to play an active role in the process of learning. That is, The teaching activity induces the elaborative and meaningful learning. This study compared the effects of our teachable agent, KORI, and peer tutoring on the cognition and motivation. The field experiment was conducted to examine whether learning by teaching the teachable agent would be more effective than peer tutoring and reading condition. In the experiment, all participants took 30 minutes lesson on rock and rock cycle together to acquire the base knowledge in the domain. After the lesson, participants were randomly assigned to one of the three experimental conditions; reading condition, peer tutoring condition, and teachable agent condition. Next, participants of each condition moved into separated place and performed their own learning activity. After finishing all of the learning activities in each condition, all participants were instructed to rate the interestingness using a 5-point scale on their own learning activity and leaning material, and were given the comprehension test. The results indicated that the teachable agent condition and the peer tutoring condition showed more interests in the learning than the reading condition. It is suggested that teachable agent has more advantages in overcoming the several practical limitations of peer tutoring such as restrictions in time and place, tutor's cognitive burden, unnecessary interaction during peer tutoring. The applicability and prospects of the teachable agent as an efficient substitute for peer tutoring and traditional intelligent tutoring system were also discussed.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.11a
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• pp.305-306
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• 2010

• 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.10 no.1
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• pp.1-11
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• 1999

Agent-based systems technology has generated lots of excitement in these years because of its promise as a new paradigm for conceptualizing. designing. and l implementing software systems Especially, there has been many researches for multi agent system because of the characteristics that it fits to the distributed and open Internet environments. In a multiagent system. agents must cooperate with each other through a Coordination procedure. when the conflicts between agents arise. where those are caused b by the point that each action acts for a purpose separately without coordination. But P previous researches for coordination methods in multi agent system have a deficiency that they can not solve correctly the cooperation problem between agents which have different goals in dynamic environment. In this paper. we solve the cooperation problem of multiagent that has multiple goals in a dynamic environment. with an automatic cooperative coordination model using I reinforcement learning. We will show the two pursuit problems that we extend a traditional problem in multi agent systems area for modeling the restriction in the multiple goals in a dynamic environment. and we have verified the validity of the proposed model with an experiment.

• The Journal of Korean Association of Computer Education
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• v.10 no.5
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• pp.43-51
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• 2007

We have developed a peer agent to support programming learning and analyzed its educational effects in a programming course. The agent acts as a tutor or a tutee. The role of a tutor/tutee is like the role of a navigator/driver in pair programming. While students are learning with the peer agent, the students' programming abilities are modeled. Based on the student's model, the peer agent provides appropriate feedbacks and contents to the learner. The peer agent gives positive effects on learners' achievement and self-efficacy in a programming course. It means that the peer agent system helps the learner in an affective domain as well as a cognitive domain.

• Natural Product Sciences
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• v.26 no.1
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• pp.1-9
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• 2020

Flavonoids are mainly contained in the vegetables and medicinal herbs. Until now, over 5,000 kinds of flavonoid have been identified and their biological activities have been reported. Among them, we are interested in oroxylin A and spinosin because of their specific structures having bulky group at C-6 of ring A. Oroxylin A is contained in the Scutellaria baicalensis and exhibits cognitive enhancing activity as a GABA_A receptor antagonist, which is different from those of mainly contained in the S. baicalenis, baicalein or wogonin. Spinosin is isolated from Zizyphus jujuba var. spinosa and mainly studied as a hypnotic or anxiolytic agent because of traditional knowledge about its original herb. As far as we know, the cognitive function of spinosin was first identified by our group. In this review, we discuss how such flavonoids exert their pharmacological activities associated with cognitive function based on the receptor binding study and behavioral studies. Traditional knowledge and reverse pharmacology may be addressed in the research field of phytochemical pharmacology and useful to unveil the secret of phytochemicals.