Service-oriented architecture for ontologies supporting multi-agent system negotiations in virtual enterprise

Nowadays, virtual enterprise (VE) is an important paradigm of business management in an agile environment. VE exists in several kinds of business organization through multi-layered product flows. It is obvious that a mechanism, through which these different enterprises can be integrated together, is required for the better management of VE. In this paper, we focus on the negotiation process in VE formulation as a basic research to clarify its effective management. Each enterprise in VE is defined as a software agent with multi-utilities, and three types of primitive business models are targeted, such as the vertically integrated business model, horizontally specialized business model and hybrid business model. We develop a three-layered VE model for computer simulation so as to clarify VE formulation dynamism with the proposed negotiation mechanism.

A New Approach In Learning For Intelligent Multi Agent Systems

When it comes to modeling social life, few paradigms are more suitable than multi-agent systems (MASs). MASs have helped gain a deeper understanding of countless social phenomena (through agent-based social simulation) that were hard to study using analytical approaches. More recently, MASs have evolved into handy assistants to the human users they can act on behalf of. One example of such use of MASs is in implementing virtual enterprises (VEs), i.e. temporary alliances of geographically distributed organizations created in order to exploit a specific business opportunity. Competition, negociation and cooperation mechanisms are usually copresent in the creation and operation of VEs, with individual members being simultaneously autonomous self-interested entities and parts of a larger whole, the benefits of which they are also trying to maximize. In turn, VEs have application areas such as commerce, manufacturing, and tourism, offering important contributions to the universal contemporary strife to obtain customer-driven products while optimizing time, costs, and quality. In this chapter, we aim to review the most important applications of MASs in social sciences, with a focus on VEs as a special case.

Virtual Enterprise (VE) is a temporary alliance of enterprises that come together in order to better respond to cope with demand of customers. VE includes many kinds of business models in term of supply chain, such as vertical structure, horizontal structure and so on. In this study, we focus on the negotiation process in VE, and try to apply multi-agent paradigm with marketing science and game theoretic approach as its decision making mechanism in order to analyse the characteristics of several business models. We propose VE simulation models to analyse the forming dynamism of VE amongst several potential members in the negotiation domain, and finally clarify the performance of VE based business models.

A critical issue in patient planning is to determine whether the medical processes of a patient can be completed by a time constraint based on the available resources in hospitals. The problem is a Temporal Constraint Satisfaction Problem (TCSP). The objectives of this paper are to propose a viable and systematic approach to develop a distributed cooperative problem solver for TCSP and estimate the shortest and the longest completion time for handling a patient in the presence of uncertainty based on Multi-agent systems (MAS) architecture. Our approach combines MAS with a subclass of time Petri net (TPN) models to solve TCSP. Existing analysis methods of TPN based on state classes cannot be applied directly due to distributed architecture of MAS. In this paper, a temporal analysis method based on MAS architecture is proposed. Our temporal analysis method efficiently deduces the earliest and latest completion time of a patient based on interaction between agents.

New advancements in computers and information technologies have yielded novel ideas to create more effective virtual collaboration platforms for multiple enterprises. Virtual enterprise (VE) is a collaboration model between multiple independent business partners in a value chain and is particularly suited to small and medium-sized enterprises (SMEs). The most challenging problem in implementing VE systems is ineffcient and inflexible data storage and management techniques for VE systems. In this research, an ontology-based multi-agent virtual enterprise (OMAVE) system is proposed to help SMEs shift from the classical trend of manufacturing part pieces to producing high-value-added, high-tech, innovative products. OMAVE targets improvement in the flexibility of VE business processes in order to enhance integration with available enterprise resource planning (ERP) systems. The architecture of OMAVE supports the requisite flexibility and enhances the reusability of the data and knowledge created in a VE system. In this article, a detailed description of system features along with the rule-based reasoning and decision support capabilities of OMAVE system are presented. To test and verify the functionality and operation of this system, a sample product was manufactured using OMAVE applications and tools with the contribution of three SMEs.

Virtual enterprise is the outcome of fierce competition in the world market. The selection of partners is one of the key factors for the success of virtual enterprises. Multi-agent system is an incompact agent federation composed of many agents, with its characteristics identical to virtual enterprises. It is, therefore, reasonable and effective to apply to the selection of enterprises' partner. The issue of trust is a hot topic in multi-agent system. The present trust model cannot well solve the problem of identifying the initial trust value of applicant agents. Moreover, there is room for improvement as to the calculation of agent trust value. This study puts forward a new trust management model based on multi-agent system. In the model, a fuzzy algorithm is used to calculate the initial value of the agent instead of a static definition. In addition, an independent validation module is used to test information reliability. Therefore, the problems of identifying initial trust value can be solved. Through system simulation, it is noted that based on the trust management model the cooperation rate has been enhanced and individual agent's income has risen by a big margin.

There is a growing recognition that current manufacturing enterprises must be agile, and the use of virtual enterprise (VE) is becoming increasingly prevalent in recent years. It is a very important and difficult activity in forming a virtual enterprise to select appropriate business partners, because each enterprise considers not only pursuing its profit but also sharing the risk to join the virtual enterprise. At first we propose a VE coalition algorithm based on multi-agent paradigm. Then we develop a computer simulation model to evaluate the proposed method by forming a virtual enterprise through multiple negotiations amongst several potential members in the negotiation domain. Finally, we clarify the coalition dynamism with the negotiation process. The effectiveness of the proposed concept in the agile manufacturing is discussed with several simulation experiments.

In an efficient Virtual Enterprise (VE), where all the partners, both sending and receiving messages have to lead to acceptable and meaningful agreements, it is necessary to have common standards (an interaction protocol to achieve deals, a language for describing the messages’ content and ontology for describing the domain’s knowledge). This paper introduces first the ForEV platform, implemented through a Multi-Agent System. This platform facilitates partners’ selection automatic process in the context of VE and includes a negotiation protocol through multi-criteria and distributed constraint formalisms, as well as a reinforcement learning algorithm. Then, Ontology-based Services are proposed to be integrated in ForEV architecture in order to help in the VE formation process. These services will make the platform more open, enabling the establishment of the negotiation process between agents with different ontologies although representing the same domain of knowledge. An Ontology-based Services Agent is the responsible for providing the Ontology-based Services and monitoring the whole agents interaction just in time, without needing of a previous and tedious complete ontology mapping process. In our architecture each agent (either market or enterprise) has its own architecture and functionalities (some developer will design and build the ontology with some tool and, later, the agent will access the generated file/database), which implies the heterogeneity of the all Multi-Agent System.

In the course of globalization competitive pressure is rising in most industrial sectors. High quality products are basic prerequisites for companies of high wage countries to be present on the global market. Improved adherence to delivery date, increased flexibility despite to decreased production costs are some examples of the challenges to be managed just to keep current positions. In general, these requirements are mostly requirements on the processes-not on the actual products. Economic efficiency is not any longer just a property of products and quality, but more and more a property of processes. Thus, process capability is getting more important beside production capability. This paper shows how service-oriented architectures (SOA) and multi-agent systems (MAS) can be integrated using a model-driven approach. In fact, a model transformation from SoaML-a metamodel for SOA-to DSML4MAS-a domain-specific modeling language for MAS-is utilized for the integration. The relevance of this approach is proven by applying it to a real-world industry scenario. This includes modeling a segment of a production chain of Saarstahl AG-a global respected steel manufacturer. The presented approach helps to increase flexibility of mid and short term planning and scheduling along the chosen segment and thus improve processes.

Semantic-based information retrieval techniques understand the meanings of the concepts that users specify in their queries, but the traditional semantic matching methods based on the ontology tree have three weaknesses which may lead to many false matches, causing the falling precision. In order to improve the matching precision and the recall of the information retrieval, this paper proposes a multi-agent improved semantic similarity matching algorithm based on the ontology tree, which can avoid the considerable computation redundancies and mismatching during the entire matching process. The results of the experiments performed on our algorithm show improvements in precision and recall compared with the information retrieval techniques based on the traditional semantic similarity matching methods.

The Intrusion Detection System architectures used in commercial and research systems have a number of problems that limit their configurability. An important problem of agents: learning is not used. The concept of learning in existing IDSs used in general to learn the normal behavior of the system to secure. Thus, the IDS does not have the ability to detect new attacks. We propose in this paper a new architecture for intrusion detection based in multi agent systems adding a learning feature abnormal behaviors that correspond to new attack patterns. We present the motivation and description of the approach, for the detection step, the approach adopted is based on the technique of Case-Based Reasoning (CBR). The proposed architecture is based on a hierarchical and distributed strategy separated into three layers. We focus after on the modeling of our Multi agent systems Architecture, for reasons of simplicity, we use the methodology O-MaSE.

Developing A Multi-Agent System in JADE for Information Management in Educational Competence Domains

In the Virtual Enterprises (VE) environment, interactions between distributed, heterogeneous computing entities representing different enterprises, people and resources, take place. These interactions, in order to be both syntactic and semantic compatible, need to follow appropriate standards (ontologies) well understood by all the participants. Even for each domain ontology, people may store their data in different structures and use different terms to represent the same concept. This paper focuses on ane effort to create an Ontology-Services Agent to monitor the communication acts taking place in a Multi-agent System. The Ontology-Services Agent provides help in solving the Structural and Semantic Heterogeneity problem, enabling appropriate conversations and making it possible meaningful agreements between agents representing different enterprises and resources in a VE environment.

Service Level Agreements (SLAs) are used in Service- Oriented Computing to define the obligations of the parties involved in a transaction. SLAs define these obligations, including for instance the expected service levels to be delivered by the provider, and the payment expected from the client. The obligations of the parties must be made explicit prior to the transaction, and a mechanism should be available to control the interaction, in order to ensure that the obligations are met. We outline a norm-oriented multiagent system (NoMAS) architecture that is combined with the service-oriented architecture in order to support the definition, management, and control of SLAs between the service clients and service providers.KeywordsSLAmanagementmutual obligationssupervisionnorm oriented multi-agent systems