• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2027-2032
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• 2003

For action selection as well as learning, simple associations between stimulus and response have been employed in most of literatures. But, for a successful task accomplishment, it is required that an animat can learn and express behavioral sequences. In this paper, we propose a novel action-selection-mechanism to deal with sequential behaviors. For this, we define behavioral motivation as a primitive node for action selection, and then hierarchically construct a network with behavioral motivations. The vertical path of the network represents behavioral sequences. Here, such a tree for our proposed ASM can be newly generated and/or updated, whenever a new sequential behaviors is learned. To show the validity of our proposed ASM, three 2-D grid world simulations will be illustrated.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.6
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• pp.606-611
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• 2014

The understanding of another's behavior is a fundamental cognitive ability for primates including humans. Recent neuro-physiological studies suggested that there is a direct matching algorithm from visual observation onto an individual's own motor repertories for interpreting cognitive ability. The mirror neurons are known as core regions and are handled as a functionality of intent recognition on the basis of imitative learning of an observed action which is acquired from visual-information of a goal-directed action. In this paper, we addressed previous works used to model the function and mechanisms of mirror neurons and proposed a computational model of a mirror neuron system which can be used in human-robot interaction environments. The major focus of the computation model is the reproduction of an individual's motor repertory with different embodiments. The model's aim is the design of a continuous process which combines sensory evidence, prior task knowledge and a goal-directed matching of action observation and execution. We also propose a biologically inspired plausible equation model.

• International Journal of Control, Automation, and Systems
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• v.6 no.6
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• pp.904-914
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• 2008

An action-selection-mechanism(ASM) has been proposed to work as a fully connected finite state machine to deal with sequential behaviors as well as to allow a state in the task program to migrate to any state in the task, in which a primitive node in association with a state and its transitional conditions can be easily inserted/deleted. Also, such a primitive node can be learned by a shortest path-finding-based reinforcement learning technique. Specifically, we define a behavioral motivation as having state-dependent value as a primitive node for action selection, and then sequentially construct a network of behavioral motivations in such a way that the value of a parent node is allowed to flow into a child node by a releasing mechanism. A vertical path in a network represents a behavioral sequence. Here, such a tree for our proposed ASM can be newly generated and/or updated whenever a new behavior sequence is learned. To show the validity of our proposed ASM, experimental results of a mobile robot performing the task of pushing- a- box-in to- a-goal(PBIG) will be illustrated.

• Journal of the Korean Society of Food Science and Nutrition
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• v.23 no.2
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• pp.287-292
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• 1994

This paper was investigated to elucidate the nitrite-scavenging action as one of biological actions of green tea extracts. Green tea extracts exhibited remarkable nitrite-scavenging action. Among the green tea extracts, steamed green tea showed higher nitrite-scavenging action than roasted green tea. Nitrite-savenging actions of gren tea extracts were hardly influenced until three times extraction with hot water. Furthermore , the nitirte-scavenging action of green tea extracts showed ph dependent , highest at pH 1.2 and lowest at pH 6.0. The nitrite -scavenging rate in sample extracts /amine /nitrite systems exhibited faster than that in amine/nitrite systems. In order to screen the nitirte-scavenging factors, samples extracts were fractionated with methanol. in both samples, methanol-soluble fractions possessed greater nitrite-scavenging action than methanol-insoluble fractions .The nitrite-scavenging action of methanol-soluble fractions increased with proportion to absorbance at 420nm and at 280nm, while that of green tea extracts increased with the contents of total phenols and absorbance at 280nm.

• Information Systems Review
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• v.8 no.1
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• pp.287-303
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• 2006

Recently, Investment on HRM, particularly, on training and development, in companies has been increased. Therefore, HR managers pay attention to action learning that has the practical effect on performance. The purpose of this study is to introduce action learning as an efficient training method and simultaneously to raise operational issues from the case study. This study analyses a training and development program applying action learning for team manager candidates in corporate Hyosung from September, 2005 to January, 2006. The findings are as follows: First, inefficient processes are thrown out by the process reengineering applying action learning. Second, the training and development activity is maximized by the integrated use of internal and external facilitators. Third, the steady support of executives and the driving force of HRD managers are considered as main success factors.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.4
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• pp.406-411
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• 2005

In this paper, we present the area-based Q-learning to search a target object using multiple robot. To search the target in Markovian space, the robots should recognize their surrounding at where they are located and generate some rules to act upon by themselves. Under area-based Q-learning, a robot, first of all, obtains 6-distances from itself to environment by infrared sensor which are hexagonally allocated around itself. Second, it calculates 6-areas with those distances then take an action, i.e., turn and move toward where the widest space will be guaranteed. After the action is taken, the value of Q will be updated by relative formula at the state. We set up an experimental environment with five small mobile robots, obstacles, and a target object, and tried to search for a target object while navigating in a unknown hallway where some obstacles were placed. In the end of this paper, we presents the results of three algorithms - a random search, area-based action making (ABAM), and hexagonal area-based Q-teaming.

• Korean Journal of Construction Engineering and Management
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• v.6 no.5 s.27
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• pp.166-176
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• 2005

The purpose of this paper is to develop a framework for construction knowledge management. Three variables of proposed framework includes knowledge class, strategic business function, and engineering data form. Several different techniques for evaluating the variables are developed in order to develop a strategic action plan for engineering knowledge management systems. The proposed framework for an action plan will contribute to develop knowledge management systems related to strategic engineering functions for construction companies.

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.9
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• pp.642-649
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• 2006

In order to recognize a situation from a environment which provides an intelligent service, we propose state-transition based situation modeling which is suitable for a low computing power and restricted resources like embedded systems, and we designed its application to a situation-action converter(SAC)which is consist of two parts; situation detector recognized wanted situations and action generator generated various control actions. Then, we implemented a situation manager for smart scheduler service by using a SAC which is installed to a ARM processor based embedded Linux evaluation board.

• International Journal of Control, Automation, and Systems
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• v.6 no.5
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• pp.689-701
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• 2008

In this paper, a fully adaptive feedforward feedback synchronized tracking control approach is developed for precision tracking control of 6 degree of freedom (6DOF) Stewart Platform. The proposed controller is designed in decentralized form for implementation simplicity. Interconnections among different subsystems and gravity effect are eliminated by the feedforward control action. Feedback control action guarantees the stability of the system. The gains of the proposed controller can be updated on line without requiring any prior knowledge of Stewart Platform manipulator. Thus the control approach is claimed to be fully adaptive. By employing cross-coupling error technology, the proposed approach can guarantee both of position error and synchronization error converge to zero asymptotically. Because the actuators work in synchronous manner, the tracking performances are improved. The corresponding stability analysis is also presented in this paper. Finally, simulation is demonstrated to verify the effectiveness of the proposed approach.

• Transactions of The Korea Fluid Power Systems Society
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• v.7 no.2
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• pp.19-26
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• 2010

The typical trunk lid system for vehicle is composed of a hinge having 4-bar link and gas lifter. Here, the energy regenerative brake of hydraulic driven systems is applied to the tail gate system for vehicle and removed the gas lifter. The new tail gate system is composed of a hydraulic pump by electric motor, a hydraulic motor, four check valves, an accumulator, a relief valve and a directional control valve. The dynamic characteristics of the hydraulic motor system, such as the surge pressure and response time, are investigated in both brake action and acceleration action. The capacity selection method of accumulator by mathematical model is based upon trial and error approach and computer simulation by AMEsim software is carried out.