• International Journal of Control, Automation, and Systems
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• v.5 no.6
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• pp.674-680
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• 2007

The probabilistic roadmap (PRM) method, which is a popular path planning scheme, for a manipulator, can find a collision-free path by connecting the start and goal poses through a roadmap constructed by drawing random nodes in the free configuration space. PRM exhibits robust performance for static environments, but its performance is poor for dynamic environments. On the other hand, reinforcement learning, a behavior-based control technique, can deal with uncertainties in the environment. The reinforcement learning agent can establish a policy that maximizes the sum of rewards by selecting the optimal actions in any state through iterative interactions with the environment. In this paper, we propose efficient real-time path planning by combining PRM and reinforcement learning to deal with uncertain dynamic environments and similar environments. A series of experiments demonstrate that the proposed hybrid path planner can generate a collision-free path even for dynamic environments in which objects block the pre-planned global path. It is also shown that the hybrid path planner can adapt to the similar, previously learned environments without significant additional learning.

• Journal of Digital Convergence
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• v.10 no.8
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• pp.53-61
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• 2012

This study investigates the determinants of continuous user intention of playing on-line games. Based on the data collected through on-line survey, we find that telepresense and commitment influence on the perceived utility of on-line games which, in turn, has effects on continuous user intention of and information sharing among on-line game players. In addition, the findings support the premise that the method of playing game and challenges influence on commitment, whereas rewards for playing game do not. As another determinant of perceived utility of on-line games, telepresense is found to be guided by diplomatic system and storytelling in on-line games.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.1
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• pp.171-176
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• 2020

Reinforcement learning is a well-known method for training an artificial software agent for a video game. Even though many reinforcement learning algorithms have been proposed, their performance was varies depending on an application area. This paper compares the performance of the algorithms when we train our reinforcement learning agent for a 2D racing game. We defined performance metrics to analyze the results and plotted them into various graphs. As a result, we found ACER (Actor Critic with Experience Replay) achieved the best rewards than other algorithms. There was 157% gap between ACER and the worst algorithm.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.1
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• pp.144-150
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• 2020

Reinforcement learning is a technology that can present successful and creative solutions in many areas. This reinforcement learning technology was used to deploy containers from cloud servers to fog servers to help them learn the maximization of rewards due to reduced traffic. Leveraging reinforcement learning is aimed at predicting traffic in the network and optimizing traffic-based fog computing network environment for cloud, fog and clients. The reinforcement learning system collects network traffic data from the fog server and IoT. Reinforcement learning neural networks, which use collected traffic data as input values, can consist of Long Short-Term Memory (LSTM) neural networks in network environments that support fog computing, to learn time series data and to predict optimized traffic. Description of the input and output values of the traffic-based reinforcement learning LSTM neural network, the composition of the node, the activation function and error function of the hidden layer, the overfitting method, and the optimization algorithm.

• Culinary science and hospitality research
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• v.24 no.3
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• pp.177-187
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• 2018

This study began with the expectation that work spirituality according to self - sacrificing leadership of a company recognized by hotel employees could positively affect superior liking and innovation behavior. The results of this study can be summarized as follows; the exercise of authority and the self - sacrifice in reward distribution are very important in the social exchange relationship. And the experience of joy and meaning, which is a behavior that meets the values, showed that it fulfilled the sense of accomplishment that the employees realized as a value, and it increased the satisfaction of pursuing the value of the boss and participating in and contributing to the world. Moreover, the hotel employees were likely to favor the bosses when they gave up or refrained from their authority or delegated to their subordinates, or when their bosses delayed or gave up rewards that had to be distributed to them. Also, self-sacrifice on the supervisor's job assignment is considered as an essential part of inducing the innovative behavior of the subordinates, regarded as desirable behavior or qualities.

• The Korean Journal of Health Service Management
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• v.10 no.3
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• pp.27-37
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• 2016

Objectives : This study was conducted to test the influence of job stress and calling on the organizational commitment of clinical nurses. Methods : 220 clinical nurses at two university hospitals in Busan were recruited. They were asked to complete a questionnaire, and 192 data sets were included in the statistical analysis. Results : The mean score of the clinical nurses' organizational commitment was 4.0. All subdomains of job stress and calling were found to have correlations with organizational commitment. The organizational system (t=-6.099, p<.001), lack of reward (t=-3.990, p<.001), purpose/meaningfulness (t=3.624, p<.001), and occupational climate (t=-3.581, p<.001) were revealed to have influences on the organizational commitment. The model was statistically significant, explaining 52.2% of the variance (F=47.808, p<.001). Conclusions : To help clinical nurses become committed to their organizations, administrators need to build fair and rational organizational systems, strengthen various types of rewards, and help nurses reconcile nursing and the meaning of their lives. In addition, every nurse should endeavor to change the nursing organizational climate which is based on vertical collectivism, to a rational climate.

• International Journal of Advanced Culture Technology
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• v.8 no.1
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• pp.128-134
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• 2020

The purpose of this study is to investigate the role and function of tokens to form a healthy blockchain-based ecosystem. Tokens must be constructed in a way that enhances their desired behavior to grow into a healthy token economy. The actions required of ecosystem participants in designing tokens should enable each individual to receive appropriate incentives (rewards) and encourage voluntary participation in taking this action. Also, all ecosystem participants must design to make the token ecosystem self-sustainable by generating profits. For example, in Bitcoin's proof-of-work method, mining is designed as a desirable behavior. Token-based services should be designed to induce multiple engagements, to design penalties for undesirable behavior, and to take into account evolutionary development potentials. Besides, the economic value of the entire token ecosystem will increase if the value that is designed and designed to take into account the revolutionary Innovation Possibility is greater than the reward amount paid to tokens. This study will contribute to presenting relevant service model by presenting how to design tokens and criteria when establishing blockchain-based service model. Future research is needed to discover new facts through a detailed comparative analysis between Tokennomics models.

• Journal of the Korean Home Economics Association
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• v.11 no.3
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• pp.314-328
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• 1973

Highly developed and Complicated modern society demands earlier development of a human intelligence. Thus the trend of ecucations nowadays has been rapid increase of efford in the field of child education. As a result experiments to find out the ways of developing child intelligence have been repeatedly carried out and various theories concerning them have been expressed. The aim of this study is to review such theories and researches. Generally, the ways how to develop child intelligence are divided into tow parts. One is by means of operating mental abilities of a child and the other is providing abundant environment to a child for the facilitation of such mental operation. A. Mental Operation The intelligence of a child is more likely to be developed by thorough and precise training of following four mental abilities. 1. Ability of classification 2. Ability of analogy 3. Ability of variation 4. Ability of inference B. Environment Child intelligence is also more likely to be developed by providing him next four environments. 1. When the parents maintaina moderate expectation and have know-ledge of the child's mental development. 2. When the parents follow the standard linguistic form and provide the child with ample opportunities for the verval expression. 3. When the parents provide tools and materials and opportunities for the cultural experiences. 4. When the parents furnish immediate rewards to the child's intellectual achievements and help him form a positive self-concept with regard to the intellectual abilities.

• Women's Health Nursing
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• v.7 no.1
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• pp.80-92
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• 2001

The labor participation rate of women are increasing, especially for married and 30 and over aged women in Korea. Marital role quality might be regarded as an influencing factor on quality of life or health status. The purpose of this study is to investigate influencing factors on quality of marital role for Korean employed women with husband. Data were collected from 323 mothers of students at 3 kindergartens, 2 elementary schools, 3 middle schools, 4 high schools in metropolitan area, during 1998.8~1998.12. they were dual-earner couples, and were employed over one year. Response rate is 62.3%. Quality of marital role was measured using Role Quality Scale developed by Park, June & Kim(1999). This instrument is based on Role Rewards and Concerns Scale of Barnett et al.(1993) for quality of marital role. Quality of marital role is made of 19 items and the subfactors are doing households, satisfaction with husband, and relationship with husband The scale has good internal consistency (Cronbach $\alpha$= 0.90). The findings of this study show that age, monthly average household income, husband's occupation, husband's attitude for wife's employment, and the perceived equity for labor division between couples are significant variables for quality of marital role. But education, career years, working hours per week, occupation, monthly average wage, and marital years are not significant. 33.81% of the variance in quality of martal role were accounted for by these variables.

• Journal of Advanced Research in Ocean Engineering
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• v.3 no.3
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• pp.136-148
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• 2017

The paper presents dual arm ROV manipulation using deep reinforcement learning. The purpose of this underwater manipulator is to investigate and excavate natural resources in ocean, finding lost aircraft blackboxes and for performing other extremely dangerous tasks without endangering humans. This research work emphasizes on a self-learning approach using Deep Reinforcement Learning (DRL). DRL technique allows ROV to learn the policy of performing manipulation task directly, from raw image data. Our proposed architecture maps the visual inputs (images) to control actions (output) and get reward after each action, which allows an agent to learn manipulation skill through trial and error method. We have trained our network in simulation. The raw images and rewards are directly provided by our simple Lua simulator. Our simulator achieve accuracy by considering underwater dynamic environmental conditions. Major goal of this research is to provide a smart self-learning way to achieve manipulation in highly dynamic underwater environment. The results showed that a dual robotic arm trained for a 3DOF movement successfully achieved target reaching task in a 2D space by considering real environmental factor.