• Journal of Intelligence and Information Systems
• /
• v.6 no.1
• /
• pp.113-128
• /
• 2000

This paper presents a first year report of an ongoing multi-year project to develop a systolic parallel simulation system for dynamic traffic assignment. The fundamental approach to the simulation is systolic parallel processing based on autonomous agent modeling. Agents continuously act on their own initiatives and access to database to get the status of the simulation world. Various agents are defined in order to populate the simulation world. In particular existing modls and algorithm were incorporated in designing the behavior of relevant agents such as car-following model headway distribution Frank-Wolf algorithm and so on. Simulation is based on predetermined routes between centroids that are computed off-line by a conventional optimal path-finding algorithm. Iterating the cycles of optimization-then-simulation the proposed system will provide a realistic and valuable traffic assignment. Gangnum-Gu district in Seoul is selected for the target are for the modeling. It is expected that realtime traffic assignment services can be provided on the internet within 3 years.

• ETRI Journal
• /
• v.45 no.5
• /
• pp.862-873
• /
• 2023

Determining whether an autonomous self-driving agent is in the middle of an intersection can be extremely difficult when relying on visual input taken from a single camera. In such a problem setting, a wider range of views is essential, which drives us to use three cameras positioned in the front, left, and right of an agent for better intersection recognition. However, collecting adequate training data with three cameras poses several practical difficulties; hence, we propose using data collected from one camera to train a three-camera model, which would enable us to more easily compile a variety of training data to endow our model with improved generalizability. In this work, we provide three separate fusion methods (feature, early, and late) of combining the information from three cameras. Extensive pedestrian-view intersection classification experiments show that our feature fusion model provides an area under the curve and F1-score of 82.00 and 46.48, respectively, which considerably outperforms contemporary three- and one-camera models.

• Journal of Digital Convergence
• /
• v.14 no.2
• /
• pp.259-264
• /
• 2016

In this paper, we proposed an arduino-based smart green house management system model and implemented it. The proposed system consists of control unit composed of sensors and arduino, agent program controlling the green house, and web applications providing user interfaces. The control unit transmits data of sensors such as temperature, humidity, illuminance, moisture, etc. to the agent program, and then the agent saves the data in its database. In reverse, control data are transmitted from agent program to control unit. Users can monitor sensed data of green houses and control actuators remotely using web. Plus, smart green house management is available by context awareness and autonomous control functions of the proposed system.

• Electronics and Telecommunications Trends
• /
• v.35 no.6
• /
• pp.137-149
• /
• 2020

Several multi-agent reinforcement learning (MARL) algorithms have achieved overwhelming results in recent years. They have demonstrated their potential in solving complex problems in the field of real-time strategy online games, robotics, and autonomous vehicles. However these algorithms face many challenges when dealing with massive problem spaces in sparse reward environments. Based on the centralized training and decentralized execution (CTDE) architecture, the MARL algorithms discussed in the literature aim to solve the current challenges by formulating novel concepts of inter-agent modeling, credit assignment, multiagent communication, and the exploration-exploitation dilemma. The fundamental objective of this paper is to deliver a comprehensive survey of existing MARL algorithms based on the problem statements rather than on the technologies. We also discuss several experimental frameworks to provide insight into the use of these algorithms and to motivate some promising directions for future research.

• The Journal of Korean Association of Computer Education
• /
• v.7 no.6
• /
• pp.77-84
• /
• 2004

This study proposed the agent system for educational information sharing using bookmark. In order to search and share the educational information effectively, we designed DAML+OIL-typed bookmark information. Proposed system in this study had the P2P type based on Client-Server type. We implemented the bookmark agent that has the intelligent characteristics, that is, automatic categorization of peers and documents, autonomous communication between agents using DAML, and delicate information searching using the ontology dictionary in Semantic Web environment. Hereafter, this study will contribute to activate sharing and searching educational information as well as proposed system will offer the important technologies for SCORM-based e-learning environment.

• Journal of Korean Society of Transportation
• /
• v.28 no.4
• /
• pp.107-118
• /
• 2010

Wireless communication technologies including vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) enable the development of more sophisticated and effective traffic information systems. This study presents a method to estimate vehicular travel times in a vehicular ad hoc network (VANET) environment. A novel feature of the proposed method is estimating individual vehicle travel times through advanced on-board units in each vehicle, referred to as self-estimated travel time in this study. The method uses travel information including vehicle position and speed at each given time step transmitted through the V2V and V2I communications. Vehicle trajectory data obtained from the VISSIM simulator is used for evaluating the accuracy of estimated travel times. Relevant technical issues for successful field implementation are also discussed.

• Journal of the Korea Society for Simulation
• /
• v.27 no.4
• /
• pp.47-60
• /
• 2018

Today's unmanned technology, which is being used in various industries, is expected to be able to make autonomous judgements as autonomous technology matures, in the long run aspects. In order to improve the usability of unmanned system in the military field, it is necessary to develop a technique for systematically and quantitatively analyzing the efficiency and effectiveness of the unmanned system by means of a substitute for the tasks performed by humans. In this paper, we propose the method of representing rule-based tactical behavior and modeling manned and unmanned reconnaissance agents that can effectively analyze the path alternatives which is required for the future armored cavalry to establish a reconnaissance mission plan. First, we model the unmanned ground vehicle, small tactical vehicle, and combatant as an agent concept. Next, we implement the proposed agent behavior rules, e.g., maneuver, detection, route determination, and combatant's dismount point selection, by NetLogo. Considering the conditions of maneuver, enemy threat elements, reconnaissance assets, appropriate routes are automatically selected on the operation area. It is expected that it will be useful in analyzing unmanned ground system effects by calculating reconnaissance conducted area, time, and combat contribution ratio on the route.

• Asia pacific journal of information systems
• /
• v.14 no.3
• /
• pp.121-144
• /
• 2004

Developing a personalized system on a user's behalf which is working around the Internet-based marketplace is one of the challenging issues in intelligent e-business, especially mobile commenrce. It has been highly recommended that such a mobile personalized system has to perceive the user's needs a priori by tracking user's current context such as location with activity and then to identify the current needs dynamically and proactively. Automatically and unobtrusively getting user's context is an inevitable feature for the development of autonomous mobile commenrce. However, personalization methodologies and their feasible architectures for context-aware mobile commerce have been so far very rare. Hence, this paper aims to propose a context-aware mobile commerce development methodology by applying agent and semantic web technologies for personalized reminder system, which is one of the mobile commerce support system. We revisited associationism to understand a buyer's need identification process and adopt the process as 'purchase based on association' to implement a personalized reminder system. Based on this approach, we have showed how the agent-based semantic web service system can be used to realize need-aware reminder system. NAMA(Need-Aware Multi-Agent), a prototype system, has been implemented to show the feasibility of the methodology and framework under mobile setting proposed in this paper. NAMA embeds bluetooth-based location tracking module and identify what a user is currently looking at through her/his mobile device such as PDA. Based on these capabilities, NAMA considers the context, user profile with preferences, and information about currently available services, to aware user's current needs and then link her/him to a set of services, which are implemented as web services.

• The KIPS Transactions:PartD
• /
• v.13D no.1 s.104
• /
• pp.37-50
• /
• 2006

In the focusing on the important of wireless internet, mobile terminal device plays a central role in tracking and coordinating terms in mobile business processing. Especially, mobile device has been considered as a key technology for embedded software and ubiquitous era. Because existing web environments is moving to wireless internet, the new concepts for wireless internet computing environments has gained increasing interest. Mobile agents provide a new abstraction for deploying over the existing infrastructures. Mobile application systems require the flexibility, adaptability, extensibility, and autonomous. New software developments methodology is required to meet the requirements. In this paper, we present an agent architectures model that allows compassable components with pluggable and independable. Our approach involves wrapping components inside a servlet. We have used the model and components to develop the PDA mobile agent.

• Journal of KIISE:Software and Applications
• /
• v.31 no.3
• /
• pp.317-331
• /
• 2004

Recently software agent has been studied as a new abstraction unit of software engineering. The agent with autonomous, adaptability and cooperation attribute is accepted as a new abstraction unit especially in distributed systems, open systems, and complex systems. However, the progress of agent research has been slow and the realization of agent programming language seems to be far distant. Because the properties of agent are diverse, the opinions of researchers can not converge to one. In this situation, software agent framework is accepted more realistic alternative solution. However the knowledge for its development doesn't have been shared among developers. So they often have to make same errors. We will help sharing of knowledge and experience by using pattern language which has been used in object technology for long times. This paper proposes a reactive agent framework pattern language and validates it based on ATAM［l］ The increase of such indirect experience can reduce the waste of resource by preventing the same try and error. So agent framework developers are able to concentrate on more essential issues. Finally quality of software agent framework will be increased.