A multi-agent system for the weighted earliness tardiness parallel machine problem

This paper studies the weighted earliness tardiness parallel machine problem where jobs have different processing times and distinct due dates. This NP hard problem arises in most just-in-time production environments. It is herein modeled as a mixed integer program, and solved using MAS^H, a deterministic heuristic based on multi-agent systems. MAS^H has three types of agents: I, G, and M. The I-agents are free jobs that need to be scheduled, whereas the G-agents are groups of jobs already assigned to machines. The M-agent acts as the system's manager of the independent intelligent I- and G-agents, which are driven by their own goals, fitness assessments, and context-dependent decision rules. The I- and G-agents employ exact and approximate approaches as part of their decisional process while the M-agent uses local search mechanisms to improve their (partial) solutions. The design of MAS^H is innovative in the way its intelligent agents determine bottleneck clusters and resolve conflicts for time slots. The numerical results provide computational evidence of the efficiency of MAS^H, whose performance on benchmark instances from the literature is superior to that of existing approaches. The success of MAS^H and its modularity make it a viable alternative to more complex manufacturing problems. Most importantly, they demonstrate the benefits of the hybridization of artificial intelligence and operations research.     

机器人足球视觉系统中的实时图像处理

视觉系统是整个机器人足球系统的重要组成部分。根据机器人足球视觉系统的特点,提出基于游程长度编码(RLE)的实时快速图像处理算法。算法使用RLE对图像进行压缩,并且在处理阶段高效识别出图像中目标的尺寸和位置。压缩阶段算法的时间复杂度与图像尺寸成线性关系,图像处理阶段算法的时间复杂度与图像中目标的个数和每个目标所占的扫描行数成线性关系。     

基于数字图像处理技术的实时检测系统*

基于在线检测系统与图像处理算法的研究,提出了一种适用于在线检测的快速胶片弊病检测算法。采用了红外光对胶片成像,并通过CCD相机采集图像信号送入计算机,通过平滑滤波、边缘提取及累加判别等处理技术,实现了对胶片弊病的识别与检测。现场调试运行表明,在卷片机车速2070 m/min的条件下,该系统运行稳定,对于黑白胶片的各种典型弊病能够正确检测,并能忽略掉胶片上可以接受的微小瑕疵,满足了实际生产的需要。     

An artificial immune system approach to CNC tool path generation

Reduced machining time and increased accuracy for a sculptured surface are both very important when producing complicated parts, so, the step-size and tool-path interval are essential components in high-speed and high-resolution machining. If they are too small, the machining time will increase, whereas if they are too large, rough surfaces will result. In particular, the machining time, which is a key factor in high-speed machining, is affected by the tool-path interval more than the step size. The present paper introduces a ‘system software’ developed to reduce machining time and increased accuracy for a sculptured surface with Non-Uniform Rational B-Spline (NURBS) patches. The system is mainly based on a new and a powerful artificial intelligence (AI) tool, called artificial immune systems (AIS). It is implemented using C programming language on a PC. It can be used as stand alone system or as the integrated module of a CNC machine tool. With the use of AIS, the impact and power of AI techniques have been reflected on the performance of the tool path optimization system. The methodology of the developed tool path optimization system is illustrated with practical examples in this paper.     

CLELIA: a multi-agent system for publishing printed and electronic media

This paper describes a multi-agent system (MAS) for automatic publication of information in both printed and electronic media. The main objective is to have a document ready to be displayed (and printed) at every stage of the workflow. This is accomplished by replacing the traditional human role of page editing by a multi-agent system composed of three different agent roles (section, page and element). Key aspects such as page aesthetics or readability are handled by using artificial intelligence techniques such as neural networks, genetic algorithms and fuzzy logic. The theoretical foundations of this system are discussed and an example of implementation using an external toolkit is described.     

Applications and environments for multi-agent systems

This paper addresses multi agent system (MAS) environments from an application perspective. It presents a structured view on environment-centric MAS applications. This comprises three base configurations, which MAS applications may apply directly or combine into a composite configuration. For each configuration, the paper presents key issues, requirements and opportunities (e.g. time management issues, real-world augmentation opportunities and state snapshot requirements). Thus, the paper delineates what environment technology may implement to serve MAS applications. Sample applications illustrate the configurations. Next, electronic institutions provide an example of an environment technology, addressing norms and laws in an agent society, already achieving some maturity. In comparison, application-domain specific environment technologies still are in embryonic stages.     

A system organization for parallel image processing

One of the problems in the development of multiprocessor systems for image analysis is the selection and efficient utilization of an interconnection network between the multiple processing units. This paper proposes a system organization centered around a class of interconnection networks and a global bus. Control schemes are developed for realizing the intertask communication requirements typically encountered in the parallel formulation of problems for image analysis. These schemes are simple, distributed and efficient. The utility of this organization is demonstrated by evaluating the performance of two applications.     

Symbiotic artificial immune system

Artificial Immune System algorithms use antibodies that fully specify the solution of an optimization, learning, or pattern recognition problem. By being restricted to fully specified antibodies, an AIS algorithm cannot make use of schemata or classes of partial solutions, while sub solutions can help a lot in faster emergence of a totally good solution in many problems. To exploit schemata in artificial immune systems, this paper presents a novel algorithm that combines traditional artificial immune systems and symbiotic combination operator. The algorithm starts searching with partially specified antibodies and gradually builds more and more specified solutions till it finds complete answers. The algorithm is compared with CLONALG algorithm on several multimodal function optimization and combinatorial optimization problems and it is shown that it is faster than CLONALG on most problems and can find solutions in problems that CLONALG totally fails.     

人工免疫系统的基本理论及其应用

介绍了生物免疫系统的工作机制与特性及人工免疫算法,且将人工免疫系统与其他智能方法进行比较.还归纳了人工免疫系统的工程应用并对人工免疫系统需深入研究的方向进行了展望.     

Environments for image processing algorithm development

The development of image processing algorithms can be greatly assisted by a software environment which is suitable for rapidly implementing and testing new ideas. This paper looks at a traditional approach to providing such an environment and highlights its weaknesses. The requirements of an ideal system are summarized and some observations are made about alternative software approaches.     

An integrated trust and reputation model for open multi-agent systems

Trust and reputation are central to effective interactions in open multi-agent systems (MAS) in which agents, that are owned by a variety of stakeholders, continuously enter and leave the system. This openness means existing trust and reputation models cannot readily be used since their performance suffers when there are various (unforseen) changes in the environment. To this end, this paper presents FIRE, a trust and reputation model that integrates a number of information sources to produce a comprehensive assessment of an agent’s likely performance in open systems. Specifically, FIRE incorporates interaction trust, role-based trust, witness reputation, and certified reputation to provide trust metrics in most circumstances. FIRE is empirically evaluated and is shown to help agents gain better utility (by effectively selecting appropriate interaction partners) than our benchmarks in a variety of agent populations. It is also shown that FIRE is able to effectively respond to changes that occur in an agent’s environment.     

Low-cost microprocessor-based image processing system

The architecture, implementation and image processing facilities of the LS10 low-cost microprocessor-based image processing system are described. The paper presents a summary of the system's attributes, and emphasis is given to their use in practical image processing applications. Results for processed Landsat satellite images are presented and described to illustrate the performance achievable from the system. To perform complex computations rapidly, fast Fourier transforms for example, a transputer-based processor has been developed. The paper shows how this sytem can be interfaced to the image processor.     

Information fusion in the immune system

Biologically-inspired methods such as evolutionary algorithms and neural networks are proving useful in the field of information fusion. Artificial immune systems (AISs) are a biologically-inspired approach which take inspiration from the biological immune system. Interestingly, recent research has shown how AISs which use multi-level information sources as input data can be used to build effective algorithms for realtime computer intrusion detection. This research is based on biological information fusion mechanisms used by the human immune system and as such might be of interest to the information fusion community. The aim of this paper is to present a summary of some of the biological information fusion mechanisms seen in the human immune system, and of how these mechanisms have been implemented as AISs.     

基于视频图像处理的交通事件检测系统

针对目前公路事件发生后不能及时有效检测与报警、事故处理延迟等不足,研究开发了一种基于视频图像处理的交通事件检测系统。利用计算机视觉与数字图像处理技术,对设置在公路上的摄像头采集的视频图像,进行事件检测算法智能处理,自动采集各种交通参数,检测交通事件并及时报警,可有效地减少交通延误,防止二次事件发生,保障道路安全。与传统交通事件检测系统相比,具有直观方便、费用低等优点,拥有良好的市场需求和实用价值。     

图像处理中间件在嵌入式系统中的设计与实现*

针对目前嵌入式系统中图片浏览功能的不足,通过分析彩色LCD显示驱动原理、图像处理技术,提出了一种图像处理中间件,并讨论了实现过程中的关键技术.实践证明该中间件方案切实可行,可以广泛应用于图像处理的嵌入式应用系统中.     

Artificial immune system inspired behavior-based anti-spam filter

This paper proposes a novel behavior-based anti-spam technology for email service based on an artificial immune-inspired clustering algorithm. The suggested method is capable of continuously delivering the most relevant spam emails from the collection of all spam emails that are reported by the members of the network. Mail servers could implement the anti-spam technology by using the “black lists” that have been already recognized. Two main concepts are introduced, which defines the behavior-based characteristics of spam and to continuously identify the similar groups of spam when processing the spam streams. Experiment results using real-world datasets reveal that the proposed technology is reliable, efficient and scalable. Since no single technology can achieve one hundred percent spam detection with zero false positives, the proposed method may be used in conjunction with other filtering systems to minimize errors.     

AgentGateway: A communication tool for multi-agent systems

With the rapid growth of multi-agent systems (MAS), there is a pressing need to communicate between different MAS. Various MAS communication standards have been proposed. However, MAS is usually designed to meet special need, thus making it difficult to follow a standard. This paper presents a tool called AgentGateway trying to solve this problem using a simple, effective approach. The tool translates messages from one MAS to intermediate XML-based messages, which then are translated to messages for another MAS. AgentGateway is scalable, meaning that new MAS can easily join it. Furthermore, it provides transparent and reliable communication. A prototype is developed that shows communication between two MAS, namely, Java Agent Template Lite (JATLite) and OAA, can be done using this approach.     

MILA – multilevel immune learning algorithm and its application to anomaly detection

T-cell-dependent humoral immune response is one of the more complex immunological events in the biological immune system, involving interaction of B cells with antigen (Ag) and their proliferation, differentiation and subsequent secretion of antibody (Ab). Inspired by these immunological principles, a Multilevel Immune Learning Algorithm (MILA) is proposed for novel pattern recognition. This paper describes the detailed background of MILA, and outlines its main features in different phases: Initialization phase, Recognition phase, Evolutionary phase and Response phase. Different test problems are studied and experimented with MILA for performance evaluation. The results show MILA is flexible and efficient in detecting anomalies and novel patterns.     

Parallel processing in an adaptable application oriented language processor

A framework for an application-oriented language processor is described which is based on a series of independent modules operating in parallel. All intermodule communication is handled by means of monitor procedures. The way in which this allows modules to be added or removed at will is discussed, and the implications of this approach for adaptable processors are described, with particular reference to the numerical control of machine tools.     

一种面向实时图像处理应用的基于非共享存储的多DSP系统设计

为了满足图像处理系统对图像处理能力和图像数据通信能力的实时要求,在分析多DSP系统的架构以及多DSP核之间通信机制的基础上,提出了一种基于非共享存储的同构多DSP系统设计。在硬件系统设计的基础上,根据实时系统的层次体系思想,实现了基于实时微内核的实时分布式操作系统DSP/BIOS。