Artificial intelligence in general and software agents in particular are recognized as computer science disciplines that aim to model or simulate so-called intelligent human behaviors such as perception, decision-maki...Artificial intelligence in general and software agents in particular are recognized as computer science disciplines that aim to model or simulate so-called intelligent human behaviors such as perception, decision-making, understanding, learning, etc. This work presents an approach to designing a generic Intelligent Agent that can be used in a multi-agent system to solve a complex problem. The generic agent that is proposed can be instantiated as a concrete agent, which is enabled with learning and autonomy capabilities by using Artificial Neural Networks. To highlight the generic aspect, the proposition is instantiated to be used in agriculture, health and education. The instantiated software agent applied in agriculture can process images in real time and detect defect on plants’ leaf. In the health field, the agent process image to diagnose breast cancer. When applied in Education, the agent can load an image of a student’s script and grade it. The performance of the designed agent system has the same accuracy as that of the respective neural networks used to instantiate them. In the educational field, the software agent has an accuracy of 98.9% and in the health field, it has an accuracy of 99.56% while in the agricultural field, it has an accuracy of 97.2%.展开更多
Development of complicated products is a project of system engineering It involves extensive and complicated knowledge,design methods and auxiliary technology Various factors affect each other So,modern product dev...Development of complicated products is a project of system engineering It involves extensive and complicated knowledge,design methods and auxiliary technology Various factors affect each other So,modern product development is a typical group problem with distributed and dynamic features It is apparent superiority to solve this problem with a multi agent system representing various knowledge domains Distributed artificial intelligence knowledge being used,the multi agent collaborative design system concept and model based on Internet environment are put forward The realizing method of product developing agents,interactive process among multi agents,and organization and implementing of the design project of the multi agent collaborative design system are discussed in detail Application examples are also presented.展开更多
The rapid expansion of enterprises makes product collaborative design （PCD） a critical issue under the distributed heterogeneous environment, but as the collaborative task of large-scale network becomes more complic...The rapid expansion of enterprises makes product collaborative design （PCD） a critical issue under the distributed heterogeneous environment, but as the collaborative task of large-scale network becomes more complicated, neither unified task decomposition and allocation methodology nor Agent-based network management platform can satisfy the increasing demands. In this paper, to meet requirements of PCD for distributed product development, a collaborative design mechanism based on the thought of modularity and the Agent technology is presented. First, the top-down 4-tier process model based on task-oriented modular and Agent is constructed for PCD after analyzing the mapping relationships between requirements and functions in the collaborative design. Second, on basis of sub-task decomposition for PCD based on a mixed method, the mathematic model of task-oriented modular based on multi-objective optimization is established to maximize the module cohesion degree and minimize the module coupling degree, while considering the module executable degree as a restriction. The mathematic model is optimized and simulated by the modified PSO, and the decomposed modules are obtained. Finally, the Agent structure model for collaborative design is put forward, and the optimism matching Agents are selected by using similarity algorithm to implement different task-modules by the integrated reasoning and decision-making mechanism with the behavioral model of collaborative design Agents. With the results of experimental studies for automobile collaborative design, the feasibility and efficiency of this methodology of task-oriented modular and Agent-based collaborative design in the distributed heterogeneous environment are verified. On this basis, an integrative automobile collaborative R＆D platform is developed. This research provides an effective platform for automobile manufacturing enterprises to achieve PCD, and helps to promote product numeralization collaborative R＆D and management development.展开更多
Collaborative design can create added value in the design and production process by bringing the benefit of team work and cooperation in a concurrent and coordinated manner. However, distributed design knowledge and p...Collaborative design can create added value in the design and production process by bringing the benefit of team work and cooperation in a concurrent and coordinated manner. However, distributed design knowledge and product data make the design process cumbersome. To facilitate collaborative design, an agent-based intelligent CAD platform is implemented. Intelligent agents are applied to the collaborative design. Adopting the JADE platform as framework, an intelligent collaborative design software (Co-Cad platform for short) is designed. In this platform, every man, design software, management software, equipment and resource is regarded as a single agent, the legacy design can be abstracted to be interaction between agents. Multimedia technology is integrated into Co-Cad platform, communication and identity authentication among collaborative designers from different areas are more convenient. Finally, an instance of collaborative design using Co-Cad platform is presented.展开更多
Complex and distributed systems are more and more associated with the application of WSN (Wireless Sensor Network) technology. The design of such applications presents important challenges and requires the assistance ...Complex and distributed systems are more and more associated with the application of WSN (Wireless Sensor Network) technology. The design of such applications presents important challenges and requires the assistance of several methodologies and tools. Multi-Agent systems (MAS) have been identified as one of the most suitable technologies to contribute to this domain due to their appropriateness for modeling distributed and autonomous complex systems. This work aims to contribute in the help of the design of WSN applications. The proposed architecture exploits the advantages of MAS for modeling WSN services, network topologies and sensor device architectures.展开更多
This paper introduces the structure of a multiagent design system with machine learning mechanism and its application in mechanical design. Firs of are it introduces a hierarchical structure of the multiagent design ...This paper introduces the structure of a multiagent design system with machine learning mechanism and its application in mechanical design. Firs of are it introduces a hierarchical structure of the multiagent design system and takes a mechanical design system as an example. This structure provides a computational platform for cooperative design and sharing learning of multiple design agents. The paper analyses the principle of design activity and puts forward the architecture and learning mechanism of a design agent in datail. The architecture of a design agent is for providing support to learning activity and is based on the analysis of the design activity This is followed by a description of the design knowledge base framework and sharing learning process of multiagent. The main advantages of the system is that complex design task can be done by multiagent in a distributed environment and leaming results can be shared by a group of design agents. This system has partly been implemented in Visual C++ based on Mechanical Desktop 2.0 environment.展开更多
This paper presents a NC layout design model based on agent. It takes each module as an autonomous entity participating in design process, and the product design process is described by the organized cooperative work ...This paper presents a NC layout design model based on agent. It takes each module as an autonomous entity participating in design process, and the product design process is described by the organized cooperative work of agents. This paper gives in detail the function and architecture of agent and the agent oriented design paradigm. The Cooperative Muti-agent NC Layout Design (CMNCD) system incorporating the strategy of concurrency can greatly increase the design efficacy. The prototype of the design model can realize some simple functions of creativity with the help of users.展开更多
Automatically mapping a requirement specification to design model in Software Engineering is an open complex problem. Existing methods use a complex manual process that use the knowledge from the requirement specifica...Automatically mapping a requirement specification to design model in Software Engineering is an open complex problem. Existing methods use a complex manual process that use the knowledge from the requirement specification/modeling and the design, and try to find a good match between them. The key task done by designers is to convert a natural language based requirement specification (or corresponding UML based representation) into a predominantly computer language based design model—thus the process is very complex as there is a very large gap between our natural language and computer language. Moreover, this is not just a simple language conversion, but rather a complex knowledge conversion that can lead to meaningful design implementation. In this paper, we describe an automated method to map Requirement Model to Design Model and thus automate/partially automate the Structured Design (SD) process. We believe, this is the first logical step in mapping a more complex requirement specification to design model. We call it IRTDM (Intelligent Agent based requirement model to design model mapping). The main theme of IRTDM is to use some AI (Artificial Intelligence) based algorithms, semantic representation using Ontology or Predicate Logic, design structures using some well known design framework and Machine Learning algorithms for learning over time. Semantics help convert natural language based requirement specification (and associated UML representation) into high level design model followed by mapping to design structures. AI method can also be used to convert high level design structures into lower level design which then can be refined further by some manual and/or semi automated process. We emphasize that automation is one of the key ways to minimize the software cost, and is very important for all, especially, for the “Design for the Bottom 90% People” or BOP (Base of the Pyramid People).展开更多
文摘Artificial intelligence in general and software agents in particular are recognized as computer science disciplines that aim to model or simulate so-called intelligent human behaviors such as perception, decision-making, understanding, learning, etc. This work presents an approach to designing a generic Intelligent Agent that can be used in a multi-agent system to solve a complex problem. The generic agent that is proposed can be instantiated as a concrete agent, which is enabled with learning and autonomy capabilities by using Artificial Neural Networks. To highlight the generic aspect, the proposition is instantiated to be used in agriculture, health and education. The instantiated software agent applied in agriculture can process images in real time and detect defect on plants’ leaf. In the health field, the agent process image to diagnose breast cancer. When applied in Education, the agent can load an image of a student’s script and grade it. The performance of the designed agent system has the same accuracy as that of the respective neural networks used to instantiate them. In the educational field, the software agent has an accuracy of 98.9% and in the health field, it has an accuracy of 99.56% while in the agricultural field, it has an accuracy of 97.2%.
基金Supported by National Nature Science Foundation of China （61074068, 60774009, 61034007）, and the Research Fund for the Doc- toral Program of Chinese Higher Education （200804220028）
基金This project is supported by National Natural Science Foundation of China (No.59875087) and by Foundation for University Key T
文摘Development of complicated products is a project of system engineering It involves extensive and complicated knowledge,design methods and auxiliary technology Various factors affect each other So,modern product development is a typical group problem with distributed and dynamic features It is apparent superiority to solve this problem with a multi agent system representing various knowledge domains Distributed artificial intelligence knowledge being used,the multi agent collaborative design system concept and model based on Internet environment are put forward The realizing method of product developing agents,interactive process among multi agents,and organization and implementing of the design project of the multi agent collaborative design system are discussed in detail Application examples are also presented.
基金Supported by National Science and Technology Major Project of China(Grant No.2009ZX04014-103)PhD Programs Foundation of Ministry of Education of China(Grant No.20100072110038)+1 种基金National Natural Science Foundation of China(Grant Nos.61075064,61034004,61005090)Program for New Century Excellent Talents in University of Ministry of Education of China(Grant No.NECT-10-0633)
文摘The rapid expansion of enterprises makes product collaborative design （PCD） a critical issue under the distributed heterogeneous environment, but as the collaborative task of large-scale network becomes more complicated, neither unified task decomposition and allocation methodology nor Agent-based network management platform can satisfy the increasing demands. In this paper, to meet requirements of PCD for distributed product development, a collaborative design mechanism based on the thought of modularity and the Agent technology is presented. First, the top-down 4-tier process model based on task-oriented modular and Agent is constructed for PCD after analyzing the mapping relationships between requirements and functions in the collaborative design. Second, on basis of sub-task decomposition for PCD based on a mixed method, the mathematic model of task-oriented modular based on multi-objective optimization is established to maximize the module cohesion degree and minimize the module coupling degree, while considering the module executable degree as a restriction. The mathematic model is optimized and simulated by the modified PSO, and the decomposed modules are obtained. Finally, the Agent structure model for collaborative design is put forward, and the optimism matching Agents are selected by using similarity algorithm to implement different task-modules by the integrated reasoning and decision-making mechanism with the behavioral model of collaborative design Agents. With the results of experimental studies for automobile collaborative design, the feasibility and efficiency of this methodology of task-oriented modular and Agent-based collaborative design in the distributed heterogeneous environment are verified. On this basis, an integrative automobile collaborative R＆D platform is developed. This research provides an effective platform for automobile manufacturing enterprises to achieve PCD, and helps to promote product numeralization collaborative R＆D and management development.
文摘Collaborative design can create added value in the design and production process by bringing the benefit of team work and cooperation in a concurrent and coordinated manner. However, distributed design knowledge and product data make the design process cumbersome. To facilitate collaborative design, an agent-based intelligent CAD platform is implemented. Intelligent agents are applied to the collaborative design. Adopting the JADE platform as framework, an intelligent collaborative design software (Co-Cad platform for short) is designed. In this platform, every man, design software, management software, equipment and resource is regarded as a single agent, the legacy design can be abstracted to be interaction between agents. Multimedia technology is integrated into Co-Cad platform, communication and identity authentication among collaborative designers from different areas are more convenient. Finally, an instance of collaborative design using Co-Cad platform is presented.
文摘Complex and distributed systems are more and more associated with the application of WSN (Wireless Sensor Network) technology. The design of such applications presents important challenges and requires the assistance of several methodologies and tools. Multi-Agent systems (MAS) have been identified as one of the most suitable technologies to contribute to this domain due to their appropriateness for modeling distributed and autonomous complex systems. This work aims to contribute in the help of the design of WSN applications. The proposed architecture exploits the advantages of MAS for modeling WSN services, network topologies and sensor device architectures.
文摘This paper introduces the structure of a multiagent design system with machine learning mechanism and its application in mechanical design. Firs of are it introduces a hierarchical structure of the multiagent design system and takes a mechanical design system as an example. This structure provides a computational platform for cooperative design and sharing learning of multiple design agents. The paper analyses the principle of design activity and puts forward the architecture and learning mechanism of a design agent in datail. The architecture of a design agent is for providing support to learning activity and is based on the analysis of the design activity This is followed by a description of the design knowledge base framework and sharing learning process of multiagent. The main advantages of the system is that complex design task can be done by multiagent in a distributed environment and leaming results can be shared by a group of design agents. This system has partly been implemented in Visual C++ based on Mechanical Desktop 2.0 environment.
文摘This paper presents a NC layout design model based on agent. It takes each module as an autonomous entity participating in design process, and the product design process is described by the organized cooperative work of agents. This paper gives in detail the function and architecture of agent and the agent oriented design paradigm. The Cooperative Muti-agent NC Layout Design (CMNCD) system incorporating the strategy of concurrency can greatly increase the design efficacy. The prototype of the design model can realize some simple functions of creativity with the help of users.
文摘Automatically mapping a requirement specification to design model in Software Engineering is an open complex problem. Existing methods use a complex manual process that use the knowledge from the requirement specification/modeling and the design, and try to find a good match between them. The key task done by designers is to convert a natural language based requirement specification (or corresponding UML based representation) into a predominantly computer language based design model—thus the process is very complex as there is a very large gap between our natural language and computer language. Moreover, this is not just a simple language conversion, but rather a complex knowledge conversion that can lead to meaningful design implementation. In this paper, we describe an automated method to map Requirement Model to Design Model and thus automate/partially automate the Structured Design (SD) process. We believe, this is the first logical step in mapping a more complex requirement specification to design model. We call it IRTDM (Intelligent Agent based requirement model to design model mapping). The main theme of IRTDM is to use some AI (Artificial Intelligence) based algorithms, semantic representation using Ontology or Predicate Logic, design structures using some well known design framework and Machine Learning algorithms for learning over time. Semantics help convert natural language based requirement specification (and associated UML representation) into high level design model followed by mapping to design structures. AI method can also be used to convert high level design structures into lower level design which then can be refined further by some manual and/or semi automated process. We emphasize that automation is one of the key ways to minimize the software cost, and is very important for all, especially, for the “Design for the Bottom 90% People” or BOP (Base of the Pyramid People).
