• Journal of Science Education
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• v.40 no.1
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• pp.1-16
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• 2016

The purpose of this study is to explore the variables of knowledge, acceptance of theory of evolution and epistemology that could be keys for teaching and learning the theory of evolution within school contexts, and to suggest instructional tips for teaching evolution in relation to the grade levels of education. This cross-sectional study examined the grade level differences (8th, 11th, and preservice teachers) of four variables: evolutionary knowledge; acceptance of theory of evolution; and both domain-specific epistemology (nature of science in relation to evolution) and context-specific epistemology (scientific epistemological views) and their relationships. This study, then, built conceptual models of each grade level students' acceptance of theory of evolution among the factors of evolutionary knowledge and epistemology (both domain-specific and context-specific). The results showed that the scores of evolutionary knowledge, evolution in relation to NOS, and scientific epistemology increased as the grade levels of education go up(p<.05) except the scores of acceptance of theory of evolution(p>.05). In addition, the 8th graders' and the 11th graders' acceptance of evolutionary theory was most explained by 'evolution in relation to NOS', while the preservice teachers' acceptance of evolutionary theory was most explained by evolutionary knowledge. Interestingly, 'scientific epistemological views' were only included for the 8th graders, while evolutionary knowledge and 'evolution in relation to NOS' (context-specific epistemology) were included in explaining all the level of students' acceptance of evolutionary theory. This study implicated that when teaching and learning of the theory of evolution in school contexts, knowledge, acceptance of evolutionary theory and epistemology could be considered appropriately for the different grade levels of students.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.3
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• pp.253-261
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• 2004

Game theory is mathematical analysis developed to study involved in making decisions. In 1928, Von Neumann proved that every two-person, zero-sum game with finitely many pure strategies for each player is deterministic. As well, in the early 50's, Nash presented another concept as the basis for a generalization of Von Neumann's theorem. Another central achievement of game theory is the introduction of evolutionary game theory, by which agents can play optimal strategies in the absence of rationality. Not the rationality but through the process of Darwinian selection, a population of agents can evolve to an Evolutionary Stable Strategy (ESS) introduced by Maynard Smith. Keeping pace with these game theoretical studies, the first computer simulation of co-evolution was tried out by Hillis in 1991. Moreover, Kauffman proposed NK model to analyze co-evolutionary dynamics between different species. He showed how co-evolutionary phenomenon reaches static states and that these states are Nash equilibrium or ESS introduced in game theory. Since the studies about co-evolutionary phenomenon were started, however many other researchers have developed co-evolutionary algorithms, in this paper we propose Game theory based Co-Evolutionary Algorithm (GCEA) and confirm that this algorithm can be a solution of evolutionary problems by searching the ESS.To evaluate newly designed GCEA approach, we solve several test Multi-objective Optimization Problems (MOPs). From the results of these evaluations, we confirm that evolutionary game can be embodied by co-evolutionary algorithm and analyze optimization performance of GCEA by comparing experimental results using GCEA with the results using other evolutionary optimization algorithms.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.4
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• pp.281-285
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• 2005

Learning and evolving are two basics for data mining. As compared with classical learning theory based on objective function with minimizing training errors, the recently evolutionary computing has had an efficient approach for constructing optimal model without the minimizing training errors. The global search of evolutionary computing in solution space can settle the local optima problems of learning models. In this research, combining co-evolving algorithm into statistical learning theory, we propose an co-evolutionary computing for statistical learning theory for overcoming local optima problems of statistical learning theory. We apply proposed model to classification and prediction problems of the learning. In the experimental results, we verify the improved performance of our model using the data sets from UCI machine learning repository and KDD Cup 2000.

• Korean Journal of Cognitive Science
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• v.28 no.3
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• pp.173-191
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• 2017

The theories of cultural evolution hold subtly or clearly different stances about definition of culture, pattern of cultural evolution, biases that affect cultural evolution, and relationship between culture and organism. However, the cultural evolution theories have a common problem to solve: As the evolutionary theory of life tries to explain the early steps and the origin of life, the cultural evolution theories also must explain the early steps of the cultural evolution and the role of the human capability that makes cultural evolution possible. Therefore, explanations of the human's unique traits including the cultural ability are related to determine which one is the most plausible among many cultural evolution theories. Theories that tried to explain human uniqueness commonly depict the coevolution of gene (organism) and culture. We will explicitly call the niche construction theory and the dual inheritance theory the 'gene-culture co-evolutionary theory'. In these theories, the most important concept is the 'concept of positive feedback'. In this paper, we distinguish between core positive feedback and marginal positive feedback, according to whether the trait that the concept of positive feedback explains is the trait of human uniqueness. Both types of positive feedback effectively explain the generality of human uniqueness and the diversity of human traits driven by cultural groups. However, this positive feedback requires an end, in contrast to negative feedback which can be continued in order to maintain homeostasis. We argue that the co-evolutionary process in the gene-culture co-evolutionary theories include only the positive feedback, not covering the cultural evolution after the positive feedback. This thesis strives to define the coevolution concept more comprehensively by suggesting the potential relationships between gene and culture after the positive feedback.

• International Journal of Control, Automation, and Systems
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• v.2 no.4
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• pp.463-474
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• 2004

Game theory is a method of mathematical analysis developed to study the decision making process. In 1928, Von Neumann mathematically proved that every two-person, zero-sum game with many pure finite strategies for each player is deterministic. In the early 50's, Nash presented another concept as the basis for a generalization of Von Neumann's theorem. Another central achievement of game theory is the introduction of evolutionary game theory, by which agents can play optimal strategies in the absence of rationality. Through the process of Darwinian selection, a population of agents can evolve to an Evolutionary Stable Strategy (ESS) as introduced by Maynard Smith in 1982. Keeping pace with these game theoretical studies, the first computer simulation of coevolution was tried out by Hillis. Moreover, Kauffman proposed the NK model to analyze coevolutionary dynamics between different species. He showed how coevolutionary phenomenon reaches static states and that these states are either Nash equilibrium or ESS in game theory. Since studies concerning coevolutionary phenomenon were initiated, there have been numerous other researchers who have developed coevolutionary algorithms. In this paper we propose a new coevolutionary algorithm named Game theory based Coevolutionary Algorithm (GCEA) and we confirm that this algorithm can be a solution of evolutionary problems by searching the ESS. To evaluate this newly designed approach, we solve several test Multiobjective Optimization Problems (MOPs). From the results of these evaluations, we confirm that evolutionary game can be embodied by the coevolutionary algorithm and analyze the optimization performance of our algorithm by comparing the performance of our algorithm with that of other evolutionary optimization algorithms.

• Industrial Engineering and Management Systems
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• v.14 no.1
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• pp.44-57
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• 2015

In recent years, for the purpose of solving the problem regarding environment protection and resource saving, certain measures and policies have been promoted to establish a reverse supply chains (RSCs) with material flows from collection of used products to reuse the recycled parts in production of products. It is necessary to analyze behaviors of RSC members to determine the optimal operation. This paper discusses a RSC with a retailer and a manufacturer and verifies the behavior strategies of RSC members which may change over time in response to changes parameters related to the recycling promotion activity in RSC. A retailer takes two behaviors: cooperation/non-cooperation in recycling promotion activity. A manufacturer takes two behaviors: monitoring/non-monitoring of behaviors of the retailer. Evolutionary game theory combining the evolutionary theory of Darwin with game theory is adopted to clarify analytically evolutionary outcomes driven by a change in each behavior of RSC members over time. The evolutionary stable strategies (ESSs) for RSC members' behaviors are derived by using the replicator dynamics. The analysis numerically demonstrates how parameters of the recycling promotion activity: (i) sale promotion cost, (ii) monitoring cost, (iii) compensation and (iv) penalty cost affect the judgment of ESSs of behaviors of RSC members.

• Proceedings of the KSME Conference
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• 2001.06b
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• pp.724-729
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• 2001

This paper discusses the composition of the theory of reinforcement learning, which is applied in real-time learning, and evolutionary strategy, which proves its the superiority in the finding of the optimal solution at the off-line learning method. The individuals are reduced in order to learn the evolutionary strategy in real-time, and new method that guarantee the convergence of evolutionary mutations are proposed. It possible to control the control object varied as time changes. As the state value of the control object is generated, applied evolutionary strategy each sampling time because the learning process of an estimation, selection, mutation in real-time. These algorithms can be applied, the people who do not have knowledge about the technical tuning of dynamic systems could design the controller or problems in which the characteristics of the system dynamics are slightly varied as time changes. In the future, studies are needed on the proof of the theory through experiments and the characteristic considerations of the robustness against the outside disturbances.

• Journal of the Korea Convergence Society
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• v.9 no.8
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• pp.185-198
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• 2018

This paper was written for the purpose of using as the theoretical basic data of judgment in the situation that there is a growing demand for intelligent design theory to be taught in public schools along with evolution theory. In order to verify the possibility that intelligent design theory, which has little empirical evidence unlike evolutionary theory, could be a scientific theory, what intelligence is and whether the trace of intelligence is actually found in nature was confirmed through literature. If intelligent elements, which are traces of intelligence in nature, are discovered empirically in nature, then intelligent design theory can be recognized as a scientific theory and can also be taught in public schools. The identity and traces of intelligence were found in relevant literature and the traces are found not only in various artificial products derived from human beings such as thinking, knowledge, and civilization, but also in all phenomena of nature. Based on these results, this paper provides a discussion on how the evolutionary theory and intelligent design theory should be handled in the field of school education, as well as how to resolve the conflicts between evolutionary theory and intelligent design theory.

• Journal of The Korean Association For Science Education
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• v.23 no.5
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• pp.470-483
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• 2003

This study analyzed the evolutionary content in 13 textbooks developed from the first to the 6th high school biology curriculum, The content analysis of textbooks, which were delineated nine component, was performed on the 80 evolutionary categories, According to the result, the proportion of the total evolutionary content in textbook increased from the textbooks developed by the Ist curriculum to the textbooks developed by the 6th curriculum, but the proportion of 'main narrative' in total evolutionary content was gradually decreased. It also showed that biology curriculum and points of view of textbook writers influenced on the proportion of evolutionary contents. On the whole, the topics of analysed textbooks exhibit insufficient diversity, Any categories- 'group selection', 'gene selection', 'gaps in fossil record', 'co-evolution', 'punctuated equilibrium', 'mosaic evolution', 'place of labor in human evolution', 'human race differentiation', 'criticism of "ontogeny recapitulates phylogeny", and 'human activities affecting evolution' - were not treated and others - 'theory of neutralism', 'theories of major episodes(excepting extinctions) found in the geologic time scale', 'sympatric speciation', 'clinal and area-effect speciation', 'polyploidy and evolution', 'gradualism' and 'evolution and origin of mammals' - were treated very lightly, the most emphasized topic was 'phylogeny in general' and 'formation of precells', 'miscellaneous' in the order of emphasis. 'Theory of natural selection' was lightly treated as just one of evolutionary theory though it should be emphasized as major theme of evolution. Also, the law of recapitulation, of which biologists doubt the validity, was discussed as an evidence of evolution in some textbooks. And the agents of genetic equilibrium disruption like genetic drift and migration were treated as of little importance. On the basis of above result, it was suggested that the textbook writers introduced the more meaningful evolutionary topics focused the theory of natural selection in explanation of evolution and evolution theory.

• 사회경제평론
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• no.38
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• pp.85-128
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• 2012

This paper aims to provide an evolutionary theory of firm existence and boundaries. We explicitly discuss about the cause of firm existence from the viewpoint of evolutionary economics, combine functionalistic and process-oriented explanation of firm evolution, and propose industry-level theory of firm boundaries. Vertical and horizontal firm boundaries are explained in the same frame.