• Journal of Korea Game Society
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• v.9 no.6
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• pp.117-125
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• 2009

This paper describes the result of applying neuro-fuzzy reasoning, which conducts Go term knowledge based on pattern knowledge, to the opening game of Go. We discuss the implementation of neuro-fuzzy reasoning for deciding the best next move to proceed through the opening game. We also let neuro-fuzzy reasoning play against TD($\lambda$) learning to test the performance. The experimental result reveals that even the simple neuro-fuzzy reasoning model can compete against TD($\lambda$) learning and it shows great potential to be applied to the real game of Go.

• Journal of the Korean earth science society
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• v.23 no.2
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• pp.154-165
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• 2002

The purpose of this study was to examine the effects of metastrategic exercise on a scientific reasoning strategy to control variables, and investigate the developmental patterns in the strategy usage within a given period. Two groups composed of 90 fifth grade students engaged in a scientific reasoning task over six daily sessions. Additionally, one group engaged in metastrategic exercise on fictional students' strategies of controlling variables on the task, while the other spent equivalent time on an unrelated task. Based upon results of the study, the following conclusions can be drawn. First, the metacognitive exercise on the strategy to control variables has positive and long-standing effects on the strategy performance at the reasoning task. The exercise also takes effect of near-transfer. Taking into consideration only about sixty minutes of metastrategic practice, the results provide the validity of the activity in order to develop children's reasoning strategies. Second, in a scientific reasoning task, each child seems to go through one out of two developmental patterns in their usage of reasoning strategies: gradual change or fundamental change. Considering the ratio of pattern of fundamental change between the two groups, it is clear that the metacognitive exercise influences the developmental pattern of strategy usage.

• Journal of the Korean Institute of Intelligent Systems
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• v.4 no.3
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• pp.32-48
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• 1994

This paper proposes the compensation algorithm of conventional shift pattern using fuzzy reasoning in automatic transmission vehicles. Recently, automatic transimssion vehicles are continually increasing because of theire ease to drive. Also users require the high performance which includes the smooth shift quality and shift scheduling that matches driver;s intentions. So the shift scheduling has been inproved significantly through the application of electronic control. But, in spite of this development, vehicles using conventional shift pattern are sometimes in discord with driver's intention on roads. In this paper, the paper, the proposed compensation algorithm makes a automatic transmission vehicle be able to select an optimal gear shifting time and position using fuzzy reasoning and make a vehicle driver feel confortable even when the vehicle runs on roads which is extremely changed. Therefore, a vehicle driver can expect to reduce the nimber of unnecessary gear shifting and expect the fuel efficiency high. To show usefulness of the proposed method, some simulation are made to compared with conventional gear shifting. Paper prosposes the compensation mehtod of conventional shift pattern using fuzzy reasoning for the purpose that a vehicle can select an optimal gerar shifting time and position in automatic vehicle. Though the conventional shift pattern has no pliability, vehicle driver can feel comfortable and can reduce the number of unnecessary gear shifting using the proposed method on variable road condition. Therefore, it can be expected the fuel efficiency.

• Journal of Korea Multimedia Society
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• v.4 no.2
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• pp.189-196
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• 2001

Fuzzy logic ignores some information in the reasoning process. Neural networks are powerful tools for the pattern processing, but, not appropriate for the logical reasoning. To model human knowledge, besides pattern processing capability, the logical reasoning capability is equally important. Another new neural network called neural logic network is able to do the logical reasoning. Because the fuzzy inference is a fuzzy logical reasoning, we construct fuzzy inference network based on the neural logic network, extending the existing rule - inference network. and the traditional propagation rule is modified.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2000.11a
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• pp.375-389
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• 2000

Fuzzy logic ignores some information in the reasoning process. Neural networks are powerful tools for the pattern processing, but, not appropriate for the logical reasoning. To model human knowledge, besides pattern processing capability, the logical reasoning capability is equally important. Another new neural network called neural logic network is able to do the logical reasoning. Because the fuzzy inference is a fuzzy logical reasoning, we construct fuzzy inference network based on the neural logic network, extending the existing rule- inference. network. And the traditional propagation rule is modified. For the search strategies to find out the belief value of a conclusion in the fuzzy inference network, we conduct a simulation to evaluate the search costs for searching sequentially and searching by means of search priorities.

• Journal of the Korean earth science society
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• v.35 no.5
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• pp.385-398
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• 2014

This study investigated students' alternative conceptions of plate boundaries and their conception revision according to the pattern of students' reasoning. Participants were twenty-two 10th grade high school students. All participants were asked to draw the three types of plate boundaries and to explain their drawings. Nine students participated in the reasoning activity. To this end, a semi-structured interview was conducted during which key questions were asked for the students to individually answer. The key questions used in the reasoning activity were created, by utilizing questions used in the previous studies. The findings revealed that the alternative conceptions of plate boundaries were classified into three levels based on established criteria. Students who attempted a variety of reasoning strategies such as causal reasoning, using an analogy, abductive reasoning, data reconstruction and concept combination, revised their alternative conception to a scientific conception after the reasoning activity. On the other hand, some students could not revise their alternative conceptions because they only conducted an incomplete reasoning strategy. The study also found that they were unable to use other reasoning strategies, either.

• Journal of Korean Elementary Science Education
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• v.23 no.1
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• pp.61-73
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• 2004

The purpose of this study was to suggest a grounded theory on the process of undergraduate students' generating pattern-knowledge about scientific episodes. The pattern-discovery tasks were administered to seven college students majoring in elementary education. The present study found that college students show five types of procedural knowledge represented in the process of pattern-discovery, such as element, elementary variation, relative prior knowledge, predictive-pattern, and final pattern-knowledge. Furthermore, subjects used seven types of thinking ways, such as recognizing objects, recalling knowledges, searching elementary variation, predictive-pattern discovery, confirming a predictive-pattern, combining patterns, and selecting a pattern. In addition, pattern-discovering process involves a systemic process of element, elementary variation, relative prior knowledge, generating and confirming predictive-pattern, and selecting final pattern-knowledge. The processes were shown the abductive and deductive reasoning as well as inductive reasoning. This study also discussed the implications of these findings for teaching and evaluating in science education.

• Asia pacific journal of information systems
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• v.14 no.3
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• pp.77-92
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• 2004

When humans make decisions, they differentiate classifications of individual attribute variables that affect the decisions according to the importance and pattern of each attribute variables. The present study examines the practicality of the proposed Code Arrangement-Based Reasoning(CABR), which resembles the human's way of reasoning. To this end, we developed a CABR technique that classifies each attribute variable affecting significant impacts on the target variable into a cluster and assigns a code to the cluster. For verifying the proposed technique, both case-based reasoning and CABR were used for the customer continuance judgment problem of an automobile insurance company. Results indicated that the performance of CABR is close to the one of the case-based reasoning. The CABR also shows the possibility of using bio-informatics techniques for organizational data analysis in the future.

• Journal of The Korean Association For Science Education
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• v.23 no.4
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• pp.309-318
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• 2003

Scientific reasoning is one of the main concerns in current science education. This study have tried to answer on the question whether Korean science education has the potential to help improve of students' ability to think scientifically. Therefore, the present study investigated the relationship between reasoning patterns evident in science textbook and science examination items, and students' scientific reasoning skills across grades in Korea. 1975 subjects (1022 females and 953 males) were administered in the Lawson's Test of Scientific Reasoning skills. Forty seven science textbooks and 240 assessment instrument were analyzed by several scientific reasoning keys. Scientific reasoning patterns were adopted from Lawson's classification which characterized the patterns as the empirical-inductive and the hypothetical-deductive. This study found that reasoning patterns evident in textbook analyses and assessment instrumental items do not evidentce the potential to stimulate the development of students' reasoning skill. In order to improve the students' abilities to think and achieve, higher levels of reasoning must be included in the science textbook and examination. Further, some of scientific reasoning processes, such as generating hypotheses, designing experiments, and logical prediction, were not found in science textbooks and test items in Korean secondary schools. This study also discussed the educational implication of these results and further studies about to develop student's reasoning ability.

• Journal of the Korean School Mathematics Society
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• v.20 no.4
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• pp.405-422
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• 2017

Nim games were divided into three stages : one file, two files and three files game, and inquiry activities were conducted for middle school mathematically gifted students. In the first stage, students easily found a winning strategy through deductive reasoning. In the second stage, students found a winning strategy with deductive reasoning or inductive reasoning, but found an error in inductive reasoning. In the third stage, no students found a winning strategy with deductive reasoning and errors were found in the induction reasoning process. It is found that the tendency to unconditionally generalize the pattern that is formed in the finite number of cases is the cause of the error. As a result of visually presenting the binary boxes to students, students were able to easily identify the pattern of victory and defeat, recognize the winning strategy through game activities, and some students could reach a stage of justifying the winning strategy.