• International Journal of Control, Automation, and Systems
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• v.6 no.3
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• pp.401-412
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• 2008

This paper discusses a design methodology of cooperative path planning for dynamical multi-agent systems with spatial and temporal constraints. The cooperative behavior of the multi-agent systems is specified in terms of the objective function in an optimization formulation. The path of achieving cooperative tasks is then generated by the optimization formulation constructed based on a differential flatness approach. Three scenarios of multi-agent tasking are proposed at the cooperative task planning framework. Given agent dynamics, both spatial and temporal constraints are considered in the path planning. The path planning algorithm first finds trajectory curves in a lower-dimensional space and then parameterizes the curves by a set of B-spline representations. The coefficients of the B-spline curves are further solved by a sequential quadratic programming solver to achieve the optimization objective and satisfy these constraints. Finally, several illustrative examples of cooperative path/task planning are presented.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.154-154
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• 2000

The cooperative strategy for the teleoperated multi-agent system is presented. And this scheme has been applied to the teleoperated robot soccer system that is newly proposed. For the teleoperated robot soccer system, we made mapping functions to control a 2-wheeled mobile robot using a 2 DoF stickcontroller. The simulation with a real stickcontroller has been evaluated the performance of the proposed mapping function. Then, the basic cooperation strategy has been tested between teleoperated robot and autonomous robot It is shown that the multi-agent system for teleoperation can have a good performance for a job Like a scoring a goal

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.3
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• pp.205-211
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• 2024

Effective warehouse management requires advanced resource planning to optimize profits and space. Robots offer a promising solution, but their effectiveness relies on embedded artificial intelligence. Multi-agent reinforcement learning (MARL) enhances robot intelligence in these environments. This study explores various MARL algorithms using the Multi-Robot Warehouse Environment (RWARE) to determine their suitability for warehouse resource planning. Our findings show that cooperative MARL is essential for effective warehouse management. IA2C outperforms MAA2C and VDA2C on smaller maps, while VDA2C excels on larger maps. IA2C's decentralized approach, focusing on cooperation over collaboration, allows for higher reward collection in smaller environments. However, as map size increases, reward collection decreases due to the need for extensive exploration. This study highlights the importance of selecting the appropriate MARL algorithm based on the specific warehouse environment's requirements and scale.

• The KIPS Transactions:PartB
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• v.10B no.1
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• pp.21-26
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• 2003

Negotiation plays a fundamental role in human cooperative activities, allowing people to resolve conflicts that could interfere with cooperative behaviors. Negotiation In multi-agent systems is achieved through the exchange of messages In a shared agent communication language (ACL). We introduce a rational negotiation meta-language for autonomous, self-interested, and resource-bounded artificial BDI agents. We then propose a negotiation protocol for BDI agents with communicative acts based on their mental states.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.05a
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• pp.333-334
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• 2010

• Journal of the Korea Society of Computer and Information
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• v.11 no.2 s.40
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• pp.285-294
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• 2006

The requirements of Computer Supported Cooperative Work supporting efficient cooperative or collaborative works between multi-users have been increasing in distributed environments. The various technical sections such as group communication technology and distributed processing technology should be provided in Cooperative Work. The replicated development of Cooperative Work applications of a number of common requirements increases development costs enormously and duplicated investment parts. Therefore, systematical development environments are required to develop these common requirements and applications efficiently in Cooperative Work applications development. In this study, we propose the hierarchical role-based coordination model that improves the coordination model of legacy mobile agent to be appropriate in Cooperative Work applications, and design the development environment for Cooperative Work applications based on mobile agent. The proposed hierarchical role-based coordination model provides multi-layered group concepts of mobile agent, and enables implementation of efficient coordination policy per group. Additionally, it supports efficient Cooperative Work application development by role assignment per group unit.

• Journal of the Korea Society of Computer and Information
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• v.29 no.1
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• pp.11-19
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• 2024

Multi-agent systems can be utilized in various real-world cooperative environments such as battlefield engagements and unmanned transport vehicles. In the context of battlefield engagements, where dense reward design faces challenges due to limited domain knowledge, it is crucial to consider situations that are learned through explicit sparse rewards. This paper explores the collaborative potential among allied agents in a battlefield scenario. Utilizing the Multi-Robot Warehouse Environment(RWARE) as a sparse reward environment, we define analogous problems and establish evaluation criteria. Constructing a learning environment with the QMIX algorithm from the reinforcement learning library Ray RLlib, we enhance the Agent Network of QMIX and integrate Random Network Distillation(RND). This enables the extraction of patterns and temporal features from partial observations of agents, confirming the potential for improving the acquisition of sparse reward experiences through intrinsic rewards.

• International Journal of Aeronautical and Space Sciences
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• v.18 no.3
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• pp.522-534
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• 2017

According to the characteristics of salvo attack for the multiple flight vehicles (MFV), the design of cooperative guidance law can be converted into the consensus problem of multi-vehicle system through the concept of multi-agent cooperative control. The flight vehicles can be divided into leader and followers depending on different functions, and the flight conditions of leader are independent of the ones of followers. The consensus problem of leader-follower multi-vehicle system is researched by graph theory, and the consensus protocol is also presented. Meanwhile, the finite time guidance law is designed for the flight vehicles via the finite time control method, and the system stability is also analyzed. Whereby, the guidance law can guarantee the line of sight (LOS) angular rates converge to zero in finite time, and hence the cooperative attack of the MFV can be realized. The effectiveness of the designed cooperative guidance method is validated through the simulation with a stationary target and a moving target, respectively.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.507-510
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• 1996

In this paper we present the multi-agent robot system developed for participating in micro robot soccer tournament. The multi-agent robot system consists of micro robot, a vision system, a host computer and a communication module. Mcro robot are equipped with two mini DC motors with encoders and gearboxes, a R/F receiver, a CPU and infrared sensors for obstacle detection. A vision system is used to recognize the position of the ball and opponent robots, position and orientation of our robots. The vision system is composed of a color CCD camera and a vision processing unit. Host computer is a Pentium PC, and it receives information from the vision system, generates commands for each robot using a robot management algorithm and transmits commands to the robots by the R/F communication module. And in order to achieve a given mission in micro robot soccer game, cooperative behaviors by robots are essential. Cooperative work between individual agents is achieved by the command of host computer.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.6
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• pp.1431-1448
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• 2024

Complexity science is a new stage in the development of systems science that is the frontier areas of contemporary scientific development. Complexity science takes complex systems as the research object, which has attracted widespread attention from researchers in the fields of economy, control, management, and society. In recent years, with the rapid development of science and technology and people's deepening understanding for the theory of complex systems, the systems are no longer an object with a single function, but the systems are composed of multiple individuals with autonomous capabilities through cooperative and cooperation, namely multi-agent system (MAS). Currently, MAS is one of the main models for studying such complex systems. The intelligent control is to break the traditional multi-agent fault-tolerant control (FTC) concept and produce a new type of compensation mechanism. In this paper, the applications of fault-tolerant control methods for MASs are presented, and a discussion is given about development and challenges in this field.