The model-based product agent: A control oriented architecture for intelligent products in multi-agent manufacturing systems

The multi-agent control strategy has been previously shown to improve the flexibility of complex, dynamic manufacturing systems. One key component of this strategy is the product agent. The product agent is responsible for autonomously guiding a physical part in the manufacturing system based on its production goals. Though the product agent has been described in previous works, a fully developed software architecture for the product agent that uses a model-based optimization approach has not been proposed. In this work, a product agent architecture with the capabilities to explore the local environment, plan and schedule events based on its knowledge, and request desired actions from the resources in the system is presented and tested.     

一种用于VoIP的负载平衡对等网络架构

针对VoIP应用,提出了一种负载平衡的对等网络架构。该架构基于Chord对等网络,采用动态更改节点标识的方法平衡各个节点上的注册用户负载。根据两个阈值,监测节点的注册用户负载量,根据负载量使用两种方法实现节点间负载的平衡,以减少节点间负载的转移对网络带宽的额外占用。仿真实验结果表明,单个节点的最大注册用户负载量和节点负载量均方差均小于Chord对等网络。基于该架构实现的对等网络,单个节点资源占用少,适于在资源受限的嵌入式VoIP终端上实现。     

Responding efficiently to relevant stimuli using an emotion-based agent architecture

It is widely accepted that one important role of emotions consists in providing a mechanism for adequate and efficient response to relevant stimuli. In this paper we propose a methodology for implementing such a mechanism, based on a previously presented emotion-based agent model. This agent model is biologically inspired in the emotion mechanisms found in the brain, following recent neurophysiological research. This model is founded on two principles: (1) stimuli is represented internally by two representations with different degrees of complexity and accuracy, and (2) the matching of these representations is implemented by a distance function. The mechanism considered in this paper amounts to matching the current stimulus the agent is perceiving with its past experience. This paper addresses a twofold strategy for optimizing the efficiency and accuracy of this mechanism. The first one consists in adapting the distance function employed in one of the representations, while the second one has the goal of upgrading that representation with new relevant features. Techniques borrowed from nonmetric multidimensional scaling are used to approach these goals.     

Hybrid artificial intelligence architecture for diagnosis and decision-making in manufacturing

This paper presents an architecture which combines artificial neural networks (ANNs) and an expert system (ES) into a hybrid, self-improving artificial intelligence (AI) system. The purpose of this project is to explore methods of combining multiple AI technologies into a hybrid intelligent diagnostic and advisory system. ANNs and ESs have different strengths and weaknesses, which can be exploited in such a way that they are complementary to each other: strengths in one system make up for weaknesses in the other, andvice versa. There is, presently, considerable interest in ways to exploit the strengths of these methodologies to produce an intelligent system which is more robust and flexible than one using either technology alone. Any process which involves both data-driven (bottom-up) and concept-driven (top-down) processing is especially well suited to displaying the capabilities of such a hybrid system. The system can take an incoming pattern of signals, as from various points in an automated manufacturing process, and make intelligent process control decisions on the basis of the pattern as preprocessed by the ANNs, with rule-based heuristic help or corroboration from the ES. Patterns of data from the environment which can be classified by either the ES or a human consultant can result in a high-level ANN being created and trained to recognize that pattern on future occurrences. In subsequent cases in which the ANN and the ES fail to agree on a decision concerning the environmental situation, the system can resolve those differences and retrain the networks and/or modify the models of the environment stored in the ES. Work on a hybrid system for perception in machine vision has been funded initially by an Oak Ridge National Laboratory seed grant, and most of the system components are operating presently in a parallel distributed computer environment.     

Intelligent agent systems for manufacturing applications

Using the concept of intelligent agents, two system approaches are described for manufacturing applications. The first is based on the rule-based object (RBO) which is associated with a production-rules knowledge base and is implementable in an object-oriented development environment such as Smalltalk-80. A proof-of-concept automated guided vehicle (AGV) system of this kind has been recently developed. The second and more advanced approach is based on the intelligent agent object (IAO) and an AGV system of this kind is currently under development. This uses a multi-agent entity termed the modulon to handle more effectively both the co-operative planning task and the local route planning task.     

Multi-agent Mediator architecture for distributed manufacturing

A generic Mediator architecture for distributed task planning and coordination has been developed using multi-agent paradigms. In this approach, agents function autonomously as independent computing processes, and dynamic virtual clusters coordinate the agent's activities and decision making. This coordination involves dynamically created coordination agents and resource agents concurrently. The Mediator architecture contains three levels of these coordination agents: the template mediator, the data-agent manager, and the active mediator. The template mediator is the top-level global coordinator. This agent contains both the templates and the cloning mechanism to create the successively lower-level agents. Task plans are decomposed successively into subtasks, which are allocated to dynamically created agent clusters coordinated through data-agent managers and active mediators. Coordination of agent activity takes place both among the clusters and within each cluster. The system dynamically adapts to evolving manufacturing tasks, with virtual agent clusters being created as needed, and destroyed when their tasks are completed. The mediator architecture and related mechanisms are demonstrated using an intelligent manufacturing scheduling application. Both the machines and the parts involved in this production system are considered as intelligent agents. These agents use a common language protocol based on the Knowledge Query Manipulation Language (KQML). The generic Mediator approach can be used for other distributed organizational systems beyond the intelligent manufacturing application it was originally developed for.     

MidCloud: an agent‐based middleware for effective utilization of replicated Cloud services

The Cloud relies heavily on resource replication to support the demands of the clients efficiently. Replicated Cloud services are distributed across large geographic areas and are accessible via the Internet. This paper describes MidCloud; an agent‐based middleware that provides Cloud clients with dynamic load balancing and fault tolerance mechanisms for effective utilization of replicated Cloud services and resources. MidCloud can be used to connect clients with multiple replicated Cloud services and provide fast and reliable service delivery from multiple replicas. Several approaches for load balancing and fault tolerance in distributed systems were introduced; however, they require prior knowledge of the environment's operating conditions and/or constant monitoring of these conditions at run time that allows the applications to adjust the load and redistribute the tasks when operational conditions change and when failures occur. These techniques work well when there is no high communication delay. Yet, this is not true in the Cloud, where data storage and computation servers are scattered all over the world and communication delays are usually very high. MidCloud deploys approaches to reduce the negative impact of high and dynamic delays on the Cloud servers and the Internet. The experimental results show the positive effects of using MidCloud to provide efficient load balancing and fault tolerance. Copyright © 2013 John Wiley & Sons, Ltd.     

Dynamic vehicle allocation control for automated material handling system in semiconductor manufacturing

The current study examines the dynamic vehicle allocation problems of the automated material handling system (AMHS) in semiconductor manufacturing. With the uncertainty involved in wafer lot movement, dynamically allocating vehicles to each intrabay is very difficult. The cycle time and overall tool productivity of the wafer lots are affected when a vehicle takes too long to arrive. In the current study, a Markov decision model is developed to study the vehicle allocation control problem in the AMHS. The objective is to minimize the sum of the expected long-run average transport job waiting cost. An interesting exhaustive structure in the optimal vehicle allocation control is found in accordance with the Markov decision model. Based on this exhaustive structure, an efficient algorithm is then developed to solve the vehicle allocation control problem numerically. The performance of the proposed method is verified by a simulation study. Compared with other methods, the proposed method can significantly reduce the waiting cost of wafer lots for AMHS vehicle transportation.     

一种基于进程剩余运行时间总和的集群动态负载平衡算法

负载的评价是集群负载平衡策略研究中的首要问题。本文总结和比较了当前使用的三类负载向量并分析了它们的优点与不足，提出了一种新的负载评价指标一进程剩余运行时间总和。测试结果表明，使用新的负载向量提高了系统的性能，缩短了任务的执行时间，取得了更好的效果。     

Emergent command and control architecture for dynamic agent communities

Dynamic multi-agent systems require some accountability mechanism to ensure goal distribution and completion. Accountability can be maintained through proper delineation of power. An organisation is well delineated when each member has an unambiguous power relationship with its peers. Since responsibility and authority follow fully de-conflicted patterns, a delineated organisation is well suited for solving problems. This paper describes a non-deterministic agent level algorithm that emergently simulates various organisational structures and maintains a well-delineated power structure. The appropriateness of this algorithm is demonstrated in a highly dynamic, poor communication network system. A metric is provided which quantifies the appropriateness of the emerging organisational structures. A structure is considered appropriate if an unambiguous chain of accountability exists leading to the human overseer of the system.     

An agent-based service-oriented integration architecture for collaborative intelligent manufacturing

The rapidly changing needs and opportunities of today's global market require unprecedented levels of interoperability to integrate diverse information systems to share knowledge and collaborate among organizations. The combination of Web services and software agents provides a promising computing paradigm for efficient service selection and integration of inter-organizational business processes. This paper proposes an agent-based service-oriented integration architecture to leverage manufacturing scheduling services on a network of virtual enterprises. A unique property of this approach is that the scheduling process of an order is orchestrated on the Internet through the negotiation among agent-based Web services. A software prototype system has been implemented for inter-enterprise manufacturing resource sharing. It demonstrates how the proposed service-oriented integration architecture can be used to establish a collaborative environment that provides dynamic resource scheduling services.     

一组移动代理的行为设计模式

模式是开发应用程序时所用方法和指导原则的总称，它表达了人们的进行软件开发过程中常用的一些设计思想，通过分析移动代理的运行过程，提出了一组行为设计模式，其核心思想就是将系统易变的部分与不变的部分进行分离，将系统不同层次的功能进行分离，具全来说，就是按照从上到下的顺序，将移动代理的行为分成任务流、协作交流和基础功能三层，并针对不同的层提出了相应的设计思想，利用这些模式，人们可以解决移动代理系统设计过程中遇到的许多问题，因此具有很高的实用价值和理论价值。     

An aspect‐oriented software architecture for code mobility

Mobile agents have come forward as a technique for tackling the complexity of open distributed applications. However, the pervasive nature of code mobility implies that it cannot be modularized using only object‐oriented (OO) concepts. In fact, developers frequently evidence the presence of mobility scattering in their system's modules. Despite these problems, they usually rely on OO application programming interfaces (APIs) offered by the mobility platforms. Such classical API‐oriented designs suffer a number of architectural restrictions, and there is a pressing need for empowering developers with an architectural framework supporting a flexible incorporation of code mobility in the agent applications. This work presents an aspect‐oriented software architecture, called ArchM, ensuring that code mobility has an enhanced modularization and variability in agent systems, and is straightforwardly introduced in otherwise stationary agents. It addresses OO APIs' restrictions and is independent of specific platforms and applications. An ArchM implementation also overcomes fine‐grained problems related to mobility tangling and scattering at the implementation level. The usefulness and usability of ArchM are assessed within the context of two case studies and through its composition with two mobility platforms. Copyright © 2008 John Wiley & Sons, Ltd.     

航管仿真训练系统运行控制的设计与实现

描述了对航管仿真系统运行控制机制的设计和实现。先对系统功能做了简要介绍,再从进程组的监控、基于多个队列的进程调度设计等方面介绍了系统的实现过程和处理细节,最后采用负载均衡算法针对系统进行了优化设计。本系统最终实现了对进程实施定位和运行监视,对控制指令采用命令优先级处理机制,使用多个队列调度进程,从而完成训练计划,较好地控制了航管仿真训练系统的运行。     

A 3-tier cooperative control architecture for multi-step semiconductor manufacturing process

In this paper, cooperative control is investigated and applied to chained processes with multiple steps and multiple tools in semiconductor manufacturing. A cooperative control architecture is proposed to optimize product quality, to improve yield, to achieve best tool performance, and to minimize throughput time. The architecture consists of three tiers: the top tier for target optimization and overall product performance, the middle tier for tool selection based on tool performance, throughput time and tool availability, and the bottom tier for tool level run-to-run control. Large data sets are collected from four individual process steps in a fabrication facility of a leading semiconductor manufacturer and the data sets are processed and lined up for the study of cooperative control. Monte Carlo simulations are carried out based on the real data to demonstrate a significant improvement for the end-of-line product quality.     

A system architecture for holonic manufacturing planning and control (EtoPlan)

In this paper, we present the system architecture of a flexible manufacturing planning and control system, named EtoPlan. The concept is based on the holonic control approach of building multiple and temporary hierarchies (holarchies). This paper describes the system architecture for flexible planning and control of activities and (groups of) Resources in a manufacture-to-order environment. The system architecture consists of generic control modules that can be applied on different hierarchical levels and for different kinds of manufacturing activities. The main function of the Resource Controller is the Determine Applicability function.     

e-Automation,an architecture for distributed industrial automation systems

Due to the complexity of modern industrial systems, a conventional automation system is not capable of providing sufficient information management and high-level intelligent approaches, as achieving these functionalities requires the support of comprehensive data management and coordination between system devices and heterogenous information. This paper proposes the concept of e-Automation, in which computer networking and distributed intelligence agent technologies are applied to industrial automation systems, and presents a hardware and software architecture that implements this concept. An open infrastructure based on multi-agent systems is employed in the proposed architecture of e-Automation, which aims to allow the implementation of diverse tasks and to permit greater configurability than can be obtained from a traditional system. To evaluate our proposed e-Automation concept, this paper presents a case study of substation information management which adopts the proposed e-Automation architecture in power system domain.     

A novel soft computing architecture for the control of autonomous walking robots

An integration of concepts from neurobiology, applied psychology, insect physiology and behaviour based robotics has led us to propose a novel generic systems architecture for the intelligent control of mobile robots and in particular, autonomous walking machines. (We define what we mean by “autonomy”.) The control architecture is hierarchical and will be described from a top-down perspective. Level one consists of interpreting a motivation and translating this into high-level commands. Once a high-level command is generated, a range of internal representations or “cognitive maps” may be employed at level two to help provide body-centred motion. At level three of the hierarchy kinematic planning is performed. The fourth level – dynamic compensation – requires feedback from the actuators and compensates for errors in the target vectors provided by the kinematic level and caused by systematic dynamic uncertainties or environmental disturbances. This is implemented using adaptive neural controllers. The interfaces will be described and results from simulation and implementation of levels 2–4 on a hexapod robot will be presented. The hierarchy employs the following soft computing techniques: evolution strategies, cognitive maps, adaptive heuristic critics, temporal difference learning and adaptive neural control using linear-equivalent neural networks.     

An intelligent agent with layered architecture for operating systems resource management

Abstract: A software agent is defined as an autonomous software entity that is able to interact with its environment. Such an agent is able to respond to other agents and/or its environment to some degree, and has some sort of control over its internal state and actions. In belief–desire–intention (BDI) theory, an agent's behavior is described in terms of a processing cycle. In this paper, based on BDI theory, the processing cycle is studied with a software feedback mechanism. A software feedback or loop‐back control mechanism can perform functions without direct external intervention. A feedback mechanism can continuously monitor the output of the system under control (the target system), compare the result against preset values (goals of the feedback control) and feed the difference back to adjust the behavior of the target system in a processing cycle. We discuss the modeling and design aspects of an autonomous, adaptive monitoring agent with layered control architecture. The architecture consists of three layers: a scheduling layer, an optimizing layer and a regulating layer. Experimental results show that the monitoring agent developed for an e‐mail server is effective.