Model driven generative domain engineering (MDGDE) is a domain engineering method aiming to develop optimized, reusable architectures, components and aspects for application engineering. Agents are regarded in MDGDE a...Model driven generative domain engineering (MDGDE) is a domain engineering method aiming to develop optimized, reusable architectures, components and aspects for application engineering. Agents are regarded in MDGDE as special objects having more autonomy, and taking more initiative. Design of the agent involves three levels of activities: logical analysis and design, physical analysis, physical design. This classification corresponds to domain analysis and design, application analysis, and application design. Agent is an important analysis and design tool for MDGDE because it facilitates development of complex distributed system—the mobile robot. According to MDGDE, we designed a distributed communication middleware and a set of event-driven agents, which enables the robot to initiate actions adaptively to the dynamical changes in the environment. This paper describes our approach as well as its motivations and our practice.展开更多
An agent in the decision support system (DSS) has to cope with quantitative analysis processing normally. However, from the view of agent working style, the agent oriented aid modeling operations need new procedure ...An agent in the decision support system (DSS) has to cope with quantitative analysis processing normally. However, from the view of agent working style, the agent oriented aid modeling operations need new procedure accepted by the agent. For example, in the distributed activity planning processes, the transforming problem description has to use a unified pattern first, then to compute the activity′s 6 time parameters, activity′s duration, entity plan scheme, optimal calculation and so on. In this paper, we propose a process manner of agent oriented modeling for the distributed activity network. The goal is to introduce an agent working procedure included model usage, multi agent cooperating, communicating among agents and interaction between system and human. Also, it included the problem representation, the initial process, agent design, transform and the computing with interaction in detail.展开更多
文摘Model driven generative domain engineering (MDGDE) is a domain engineering method aiming to develop optimized, reusable architectures, components and aspects for application engineering. Agents are regarded in MDGDE as special objects having more autonomy, and taking more initiative. Design of the agent involves three levels of activities: logical analysis and design, physical analysis, physical design. This classification corresponds to domain analysis and design, application analysis, and application design. Agent is an important analysis and design tool for MDGDE because it facilitates development of complex distributed system—the mobile robot. According to MDGDE, we designed a distributed communication middleware and a set of event-driven agents, which enables the robot to initiate actions adaptively to the dynamical changes in the environment. This paper describes our approach as well as its motivations and our practice.
文摘An agent in the decision support system (DSS) has to cope with quantitative analysis processing normally. However, from the view of agent working style, the agent oriented aid modeling operations need new procedure accepted by the agent. For example, in the distributed activity planning processes, the transforming problem description has to use a unified pattern first, then to compute the activity′s 6 time parameters, activity′s duration, entity plan scheme, optimal calculation and so on. In this paper, we propose a process manner of agent oriented modeling for the distributed activity network. The goal is to introduce an agent working procedure included model usage, multi agent cooperating, communicating among agents and interaction between system and human. Also, it included the problem representation, the initial process, agent design, transform and the computing with interaction in detail.