A study of train group operation multi-agent model oriented RITS

In this paper, aiming at describing interrelationships and communication mechanisms among agents based on a multi-agent framework of Railway Intelligent Transportation System (RITS), we construct the model about stations and trains in the system, which is called Agent-Oriented G-Net Train Group Operation Model (AGNTOM). The framework degrades the complexity of computation and makes the distribution of simulation system easy in design. The simulated experiments prove that the model provides an effective approach for dealing with communication problems in the system.

Agent-Based Hybrid Intelligent Systems: An Agent-Based Framework for Complex Problem Solving

Pt. I. Fundamentals of hybrid intelligent systems and agents -- 1. Introduction -- 2. Basics of hybrid intelligent systems -- 3. Basics of agents and multi-agent systems -- Pt. II. Methodology and framework -- 4. Agent-oriented methodologies -- 5. Agent-based framework for hybrid intelligent systems --6. Matchmaking in middle agents -- Pt. III. Application systems -- 7. Agent-based hybrid intelligent system for financial investment
planning -- 8. Agent-based hybrid intelligent system for data mining -- Pt. IV. Concluding remarks -- 9. The less the more -- App. Sample source codes of the agent-based financial planning system

Object oriented finite element analysis: a distributed approach to mesh generation

The object-oriented finite element method (OOFEM) has attracted the attention of many researchers. Compared with the traditional finite element method, OOFEM software has the advantages of maintenance and reuse. Moreover, it is easier to expand the architecture to a distributed one. In this paper, we introduce a distributed architecture of a object-oriented finite element preprocessor. A comparison between the distributed system and the centralised system shows that the former, presented in the paper, greatly improves the performance of mesh generation. Other finite element analysis modules could be expanded according to this architecture.

The design and development of an integrated system for object-oriented finite element computing

Finite Element Method (FEM) is widely used in Science and Engineering since 1960’s. The vast majority of FEM software is procedure-oriented. However, this conventional style of designing FEM software encounters problems in maintenance, reuse, and expansion of the software. Recently the object-oriented finite element method attracts the attention of lots of researchers, and now there is a growing interest in this method. In this paper, the object-oriented finite element (OOFE) is briefly introduced. Then the design and development of an integrated OOFE system is described. A comparison of the integrated OOFE system and a procedure-oriented system shows that our OOFE system has many advantages.

A scalable and robust framework for agent-based heterogeneous database operation

How to operate database efficiently and unfailingly in agent-based heterogeneous data source environment is becoming a big problem. In this paper, we contribute a framework and develop a couple of agent-oriented matchmakers with logical ring organization structure to match task agents' requests with middleware agents of databases. The middleware agent is a wrapper of a specific database and is run on the same server with the database management system. The matchmaker is of the features of proliferation and self-cancellation according to the sensory input from its environment. The ring-based coordination mechanism of matchmakers is designed. Two kinds of matchmakers, namely, host and duplicate, are designed for improving the scalability and robustness of agent-based system. The middleware agents are improved for satisfying the framework. We demonstrate the potentials of the framework by case study and present theoretical and empirical evidence that our approach is scalable and robust.

Agent-based hybrid framework for decision making on complex problems

Electronic commerce and the Internet have created demand for automated systems that can make complex decisions utilizing information from multiple sources. Because the information is uncertain, dynamic, distributed, and heterogeneous in nature, these systems require a great diversity of intelligent techniques including expert systems, fuzzy logic, neural networks, and genetic algorithms. However, in complex decision making, many different components or sub-tasks are involved, each of which requires different types of processing. Thus multiple such techniques are required resulting in systems called hybrid intelligent systems. That is, hybrid solutions are crucial for complex problem solving and decision making. There is a growing demand for these systems in many areas including financial investment planning, engineering design, medical diagnosis, and cognitive simulation. However, the design and development of these systems is difficult because they have a large number of parts or components that have many interactions. From a multi-agent perspective, agents in multi-agent systems (MAS) are autonomous and can engage in flexible, high-level interactions. MASs are good at complex, dynamic interactions. Thus a multi-agent perspective is suitable for modeling, design, and construction of hybrid intelligent systems. The aim of this thesis is to develop an agent-based framework for constructing hybrid intelligent systems which are mainly used for complex problem solving and decision making. Existing software development techniques (typically, object-oriented) are inadequate for modeling agent-based hybrid intelligent systems. There is a fundamental mismatch between the concepts used by object-oriented developers and the agent-oriented view. Although there are some agent-oriented methodologies such as the Gaia methodology, there is still no specifically tailored methodology available for analyzing and designing agent-based hybrid intelligent systems. To this end, a methodology is proposed, which is specifically tailored to the analysis and design of agent-based hybrid intelligent systems. The methodology consists of six models - role model, interaction model, agent model, skill model, knowledge model, and organizational model. This methodology differs from other agent-oriented methodologies in its skill and knowledge models. As good decisions and problem solutions are mainly based on adequate information, rich knowledge, and appropriate skills to use knowledge and information, these two models are of paramount importance in modeling complex problem solving and decision making. Follow the methodology, an agent-based framework for hybrid intelligent system construction used in complex problem solving and decision making was developed. The framework has several crucial characteristics that differentiate this research from others. Four important issues relating to the framework are also investigated. These cover the building of an ontology for financial investment, matchmaking in middle agents, reasoning in problem solving and decision making, and decision aggregation in MASs. The thesis demonstrates how to build a domain-specific ontology and how to access it in a MAS by building a financial ontology. It is argued that the practical performance of service provider agents has a significant impact on the matchmaking outcomes of middle agents. It is proposed to consider service provider agents' track records in matchmaking. A way to provide initial values for the track records of service provider agents is also suggested. The concept of ‘reasoning with multimedia information’ is introduced, and reasoning with still image information using symbolic projection theory is proposed. How to choose suitable aggregation operations is demonstrated through financial investment application and three approaches are proposed - the stationary agent approach, the token-passing approach, and the mobile agent approach to implementing decision aggregation in MASs. Based on the framework, a prototype was built and applied to financial investment planning. This prototype consists of one serving agent, one interface agent, one decision aggregation agent, one planning agent, four decision making agents, and five service provider agents. Experiments were conducted on the prototype. The experimental results show the framework is flexible, robust, and fully workable. All agents derived from the methodology exhibit their behaviors correctly as specified.

A multi-agent incremental negotiation scheme for meetings scheduling

We present an agent-oriented approach to the meeting scheduling problem and propose an incremental negotiation scheme that makes use of a hierarchical structure of an individual agent's working knowledge. First, we formalise the meeting scheduling problem in a multi-agent context, then elaborate on the design of a common agent architecture of all agents in the system. As a result, each agent becomes a modularised computing unit yet possesses high autonomy and robust interface with other agents. The system reserves the meeting participants' privacy since there are no agents with dominant roles, and agents can communicate at an abstract level in their hierarchical structures

Object oriented regular expressions

Regular expressions are used to parse textual data to match patterns and extract variables. They have been implemented in a vast number of programming languages with a significant quantity of research devoted to improving their operational efficiency. However, regular expressions are limited to finding linear matches. Little research has been done in the field of object-oriented results which would allow textual or binary data to be converted to multi-layered objects. This is significantly relevant as many of todaypsilas data formats are object-based. This paper extends our previous work by detailing an algorithmic approach to perform object-oriented parsing, and provides an initial study of benchmarks of the algorithms of our contribution

Eiffel assertions and the external structure of classes and objects

The “external structure” in an object oriented system refers here to the  graphs of objects and classes. The class structure graph or class model is derived from the object structure graph or object model, and in this operation structural information is lost, or never made explicit. Although object oriented programming languages capture the class model as declarations,  contradictory assumptions about object model properties may be made introducing faults into the design. Consistent assumptions about the object model can be specified in the code using assertions such as Eiffel’s  invariants, preconditions and postconditions. Three examples specifying the external structure are considered.

Design of user interfaces for job shop environment

User-computer interface development has gone through rapid development in recent years. These developments, however, have not yet been fully implemented in management information system (MIS) design for job shop manufacturing situations. Most of the commercially available MISs are operationally inflexible and do not support management in report generation and decision making, particularly in job shops. This paper describes a framework in developing system user interfaces for job shop manufacturing situations to highlight how a generic information system can be made more useful to managerial decision making. Object-oriented programming technology has been used to provide flexible access to information stored by a generic MIS. Twenty interfacing programs have been developed. For illustration, only three of those interface programs relating to generation of strategic level management reports are discussed here.

Management information systems in job shops : design of interfaces

A study of management information system technology suitable for the job shop environment, highlighting deficiencies in generic software with respect to supplying users the information they actually require. To solve this problem a set of flexible interfaces was developed through the use of object-oriented programming. The methods used were simple enough to be adopted by vendors of any generic MIS application.

Adaptable, model-driven security engineering for SaaS cloud-based applications

Software-as-a-service (SaaS) multi-tenancy in cloud-based applications helps service providers to save cost, improve resource utilization, and reduce service customization and maintenance time. This is achieved by sharing of resources and service instances among multiple "tenants" of the cloud-hosted application. However, supporting multi-tenancy adds more complexity to SaaS applications required capabilities. Security is one of these key requirements that must be addressed when engineering multi-tenant SaaS applications. The sharing of resources among tenants - i.e. multi-tenancy - increases tenants' concerns about the security of their cloud-hosted assets. Compounding this, existing traditional security engineering approaches do not fit well with the multi-tenancy application model where tenants and their security requirements often emerge after the applications and services were first developed. The resultant applications do not usually support diverse security capabilities based on different tenants' needs, some of which may change at run-time i.e. after cloud application deployment. We introduce a novel model-driven security engineering approach for multi-tenant, cloud-hosted SaaS applications. Our approach is based on externalizing security from the underlying SaaS application, allowing both application/service and security to evolve at runtime. Multiple security sets can be enforced on the same application instance based on different tenants' security requirements. We use abstract models to capture service provider and multiple tenants' security requirements and then generate security integration and configurations at runtime. We use dependency injection and dynamic weaving via Aspect-Oriented Programming (AOP) to integrate security within critical application/service entities at runtime. We explain our approach, architecture and implementation details, discuss a usage example, and present an evaluation of our approach on a set of open source web applications.

Adaptive security for software systems

With continuously changing operational and business needs, system security is one of the key system capabilities that need to be updated as well. Most security engineering efforts focus on engineering security requirements of software systems at design time and existing adaptive security engineering efforts require complex design-time preparation. In this chapter we discuss the needs for adaptive software security, and key efforts in this area. We then introduce a new runtime adaptive security engineering approach, which enables adapting software security capabilities at runtime based on new security objectives, risks/threats, requirements as well as newly reported vulnerabilities. We categorize the source of adaptation in terms of manual adaptation (managed by end users), and automated adaption (automatically triggered by the platform). The new platform makes use of new ideas we built for vulnerability analysis, security engineering using aspect-oriented programming, and model-driven engineering techniques.

Dynamic reconfiguration of multi-agent systems based on autonomy oriented computing

Dynamic reconfiguration has been listed as one of the key challenges in support of agent adaptation to environments, which has attracted much attention of researchers world wide. To tackle this tough problem, an agent-based dynamic reconfiguration model (ADRM) is proposed from the autonomy-oriented computing (AOC) point of view. The ERA (environment-reactive rules-agents) algorithm used in AOC is improved to support the organization formation behavior, which is essential in dynamic reconfiguration. To test the efficiency of this model and the effectiveness of different reactive behaviors, the performance of this model was investigated under different selection probabilities.