• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.601-606
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• 1998

In this paper, we propose a new design method of an optimal fuzzy logic controller using co-evolutionary concept. In general, it is very difficult to find optimal fuzzy rules by experience when the input and/or output variables are going to increase. Futhermore proper fuzzy partitioning is not deterministic ad there is no unique solution. So we propose a co-evolutionary method finding optimal fuzzy rules and proper fuzzy membership functions at the same time. Predator-Prey co-evolution and symbiotic co-evolution algorithms, typical approaching methods to co-evolution, are reviewed, and dynamic fitness landscape associated with co-evolution is explained. Our algorithm is that after constructing two population groups made up of rule base and membership function, by co-evolving these two populations, we find optimal fuzzy logic controller. By applying the propose method to a path planning problem of autonomous mobile robots when moving objects applying the proposed method to a pa h planning problem of autonomous mobile robots when moving objects exist, we show the validity of the proposed method.

• 한국생물공학회:학술대회논문집
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• 2001.11a
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• pp.578-581
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• 2001

A treatability study was conducted using a hydrocarbon-contaminated soil for the oPtimization of bioremediation strategy best fit to a given set of contamination. The applicability of nutrients, biosurfactant, and oil-degrading microorganisms were examined by monitoring $CO_2$ evolution and oil degradation The addition of inorganic nutrients in the form of slow released fertilizer accelerated the initial rate of $CO_2$ evolution by a factor of 3. The application of oil-degrading microorganisms did not significantly increased $CO_2$ evolution or biodegradation efficiency. Application of a commercial biosurfactant was most effect in terms of the total $CO_2$ evolution and the oil degradation rate. The results indicate that $CO_2$ evolution measurement was found to be a simple and reliable countermeasure of crude oil hydrocarbon mineralization for the rapid determination of the best-fit bioremediation strategy.

• The Journal of the Korea Contents Association
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• v.14 no.11
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• pp.549-557
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• 2014

Recently, analysis of bargaining game using evolutionary computation is essential issues in field of game theory. In this paper, we observe a bargaining game using co-evolution between two heterogenous artificial agents. In oder to model two artificial agents, we use a particle swarm optimization and a differential evolution. We investigate algorithm parameters for the best performance and observe that which strategy is better in the bargaining game under the co-evolution between two heterogenous artificial agents. Experimental simulation results show that particle swarm optimization outperforms differential evolution in the bargaining game.

• 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.

• Korean Management Science Review
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• v.29 no.3
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• pp.169-182
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• 2012

This study examines the co-evolutionary process between open innovation and firms' absorptive capacity. The effects of open innovation can be maximized through the capacity to absorb the knowledge from the external sources such as universities, government-support research institute, and private R&D centers. This study used data of STEPI technology innovation survey conducted at 2002, 2005, and 2008 (3 points measures). The data were analyzed through a structural equation model. Results suggest that open innovation at t0 point influences positively the absorptive capacity at t1 point, which subsequently enhances the intention of open innovation at t2 point. This result suggests the existence of co-evolutionary process between open innovation and firms' absorptive capacity. When knowledge comes from universities, the co-evolution has sustained; whereas when knowledge comes from private firms' R&D centers, the co-evolution has not effected. Theoretical and practical implications are discussed.

• Journal of Technology Innovation
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• v.28 no.4
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• pp.63-93
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• 2020

We suggest a new way of specifying the co-evolution of product and process technologies, and integrating it into one of the well-received technology intelligence tools - a technology radar. Cross impact analysis enables us to identify the core technologies of product-process co-evolution. Combining expert judgment with its results, we can clarify the technological co-evolution trajectory with mainstream as well as emerging core technologies. Reflecting these in the assessment process of a technology radar, we could improve reliance of the technology assessment process and technology portfolio. From the academic perspective, our research provides a point where the co-evolution theory encouners technology intelligence methods. Practically, strategic capability of future-preparedness and strategic management could improve by adopting our method based on our example of co-evolution of semiconductor product and process technologies.

• Journal of Korean Society for Atmospheric Environment
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• v.12 no.3
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• pp.307-314
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• 1996

The rate of evolution of ethylent by tomato plants was rapidly increased by ozone fumigation. In the present study, the mechanism of ethylent evolution by ozone was investigated in experiments with aminoethoxyvinylglycine (AVG) and tiron, which inhibit the formation of ethylene and peroxidation of lipids, respectively. Pretreatment with AVG significantly inhibited the ozone-induced ethylent evolution, but the treatment of plants with tiron did not inhibit. These results indicate that the induction of the evolution of ethylene by ozone involves the pathway via aminocyclopropane-1-carboxylate (ACC), while not released as a result of the peroxidation of lipids. Ozone-induced ethylent evolution was greater in dar- than light-incubated, intact tomato plants. The difference between dark- and light-ethylene evolution was examined with diuron, an inhibitor of photosynthetic electron transport. The inhibitor treatment promoted ethylent evolution. These results suggest that ethylent retention and metabolism in plants were regulated by internal $CO_2$ levels which, in turn, were controlled in large part by photosynthesis. Thus, ethylene was retained in illuminated leaf tissue under low intenal $CO_2$ concentration which may develop in a sealed container without exogenously supplied $CO_2$.

• Journal of Communications and Networks
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• v.4 no.4
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• pp.336-343
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• 2002

A major challenge for next generation mobile communication is capturing the system architecture’s complexity with all its internal and external dependencies. Seamless integration of heterogeneous environments in all system parts is a key requirement. Moreover, future systems have to consider the different evolution cycles of individual system parts. Among those, services are expected to change the fastest. With respect to these considerations, we propose an overall architecture for next generation mobile communication systems. It covers all system parts from wireless transmission to applications including network and middleware platform. Our approach focuses on adaptability in terms of recon- figurability and programmability to support unanticipated system evolution. Therefore, we consider abstraction layers which consist of adaptable cooperating components grouped by open platforms rather than rigid system layers. In addition to that, we introduce cross-layer cooperation allowing an efficient use of the available resources. Specific scenarios illustrate the feasibility of our approach.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.2 no.1
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• pp.95-110
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• 1998

Evolutionary Algorithms (EAs) are population-based optimization methods based on the principle of Darwinian natural selection. The representative methodology in EAs is genetic algorithm (GA) proposed by J. H. Holland, and the theoretical foundations of GA are the Schema Theorem and the Building Block Hypothesis. In the meaning of these foundational concepts, simple genetic algorithm (SGA) allocate more trials to the schemata whose average fitness remains above average. Although SGA does well in many applications as an optimization method, still it does not guarantee the convergence of a global optimum in GA-hard problems and deceptive problems. Therefore as an alternative scheme, there is a growing interest in a co-evolutionary system, where two populations constantly interact and co-evolve in contrast with traditional single population evolutionary algorithm. In this paper we show why the co-evolutionary algorithm works better than SGA in terms of an extended schema theorem. And predator-prey co-evolution and symbiotic co-evolution, typical approaching methods to co-evolution, are reviewed, and dynamic fitness landscape associated with co-evolution is explained. And the experimental results show a co-evolutionary algorithm works well in optimization problems even though in deceptive functions.

• Korean Journal of Soil Science and Fertilizer
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• v.27 no.4
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• pp.290-295
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• 1994

Soil $CO_2$ evolution was measured using the soda-lime method for 20-year-old L. tulipifera, P. albaglandulosa, and Q. rubra plantations planted on a similar soil type in the Kwangneung Experimental Forest during the growing season of 1994. Soil $CO_2$ evolution ranged from $0.21g/m^2/hr$ for Q. rubra to $0.33g/m^2/hr$ for L. tulipifera. and was significantly different among species. We found positive correlations between soil $CO_2$ evolution and air(p<0.001, r=0.39) and soil temperatures(p<0.001, r=0.49). Peaks in seasonal soil $CO_2$ evolution occurred in July and August. Seasonal soil $CO_2$evolution did not necessarily follow changes in air and soil temperatures. This study implies that more work is needed to clarify the influence of other factors on soil $CO_2$evolution.