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

This paper offers a service-oriented architecture (SOA) for ontology-based multi-agent system (MAS) negotiations in the context of virtual enterprises (VEs). The objective of this paper is fourfold. First, it is to design a SOA which utilizes ontology and MAS to provide a distributed and interoperable environment for automated negotiations in VE. In this architecture, individual ontologies for both the VE initiator and its potential partners are constructed to describe and store resources and service knowledge. Second, a series of semantic ontology matching methods are developed to reach agents’ interoperability during the negotiation process. Third, correspondence-based extended contract net protocol is presented, which provides basic guidelines for agents’ reaching mutual understandings and service negotiation. Last, a fuzzy set theory based knowledge reuse approach is proposed to evaluate the current negotiation behaviors of the VE partners. A walkthrough example is presented to illustrate the methodologies and system architecture proposed in this paper.     

An ontology based approach to organize multi-agent assisted supply chain negotiations

Effective supply chain management (SCM) comprises activities involving the demand and supply of resources and services. Negotiation is an essential approach to solve conflicting transaction and scheduling problems among supply chain members. The multi-agent system (MAS) technology has provided the potential of automating supply chain negotiations to alleviate human interactions. Software agents are supposed to perform on behalf of their human owners only when equipped with sophisticated negotiation knowledge. To better organize the negotiation knowledge utilized by agents and facilitate agents’ adaptive negotiation decision making ability, an ontology-based approach is proposed in this paper. Firstly, the multi-agent assisted supply chain negotiation scheme is presented to configure the general design components of the negotiation system, covering the agent intelligence modules, the knowledge organization method and the negotiation protocol. Then, the ontology-based negotiation knowledge organization method is specified. The negotiation knowledge is separated into shared negotiation ontology and private negotiation ontology to ensure both the agent communicative interoperability and the privacy of strategic knowledge. Inference rules are defined on top of the private negotiation ontology to guide agents’ reasoning ability. Through this method, agents’ negotiation behaviors will be more adaptive to various negotiation environments utilizing corresponding negotiation knowledge.     

1-多交互协议本体的描述

基于本体的共享与重用性以及谈判过程的动态性,提出谈判协议过程本体,将语义Web应用到自动谈判中,利用描述逻辑和本体编辑器Protégé 3.2.1对1-多交互协议本体进行形式化描述,并得到相应的OWL文件。     

A Real-Time Negotiation Model and A Multi-Agent Sensor Network Implementation

This paper describes a negotiation model that incorporates real-time issues for autonomous agents. This model consists of two important ideas: a real-time logical negotiation protocol and a case-based negotiation model. The protocol integrates a real-time Belief-Desire-Intention (BDI) model, a temporal logic model, and communicative acts for negotiation. This protocol explicitly defines the logical and temporal relationships of different knowledge states, facilitating real-time designs such as multi-threaded processing, state profiling and updating, and a set of real-time enabling functional predicates in our implementation. To further support the protocol, we use a case-based reasoning model for negotiation strategy selection. An agent learns from its past experience by deriving a negotiation strategy from the most similar and useful case to its current situation. Guided by the strategy, the agent negotiates with its partners using an argumentation-based negotiation protocol. The model is time and situation aware such that each agent changes its negotiation behavior according to the progress and status of the ongoing negotiation and its current agent profile. We apply the negotiation model to a resource allocation problem and obtain promising results.     

电子商务中的自动协商

描述电子商务中基于智能体的自动协商，给出基于智能体的自动协商模型和协商智能体的体系结构，描述了一组构成协商协议的通信原语。通过约束满足机制、协商策略和提议评估算法实现自动协商。并实现了一个供应链管理中买卖自动协商的原型系统。     

A BDI Assignment Protocol With New Cooperative-Concession Strategies

This paper addresses the collaborative linear- assignment problem (CLAP) for a class of allocation applications. CLAP entails using agents to seek a concurrent allocation of one different object for every agent, to optimize a linear sum efficiency function as their (soft) social goal. Anchoring in the standard framework of automated negotiation allows an original belief-desire-intention (BDI) negotiation model for CLAP to be conceptually separated into a BDI assignment protocol and an adopted strategy. Facilitated by this conceptual separation, the contributions of this paper are as follows: 1) providing a rigorous analysis of the protocol and demonstrating its salient properties and 2) formulating new strategies using a novel idea of cooperative concession. Four different strategies for a negotiation agent and the arbitration agent provide 16 arbitration-negotiation combinations running with the protocol, and these are empirically assessed for their performance profiles in negotiation speed and solution quality. Important findings, including the stability of the protocol in producing better than good enough global allocations and the strategic influence of cooperative concessions on performance, are examined. The significance and practicality of this paper in relation to existing work are also discussed.     

Negotiation among autonomous computational agents: principles,analysis and challenges

Automated negotiation systems with software agents representing individuals or organizations and capable of reaching agreements through negotiation are becoming increasingly important and pervasive. Examples, to mention a few, include the industrial trend toward agent-based supply chain management, the business trend toward virtual enterprises, and the pivotal role that electronic commerce is increasingly assuming in many organizations. Artificial intelligence (AI) researchers have paid a great deal of attention to automated negotiation over the past decade and a number of prominent models have been proposed in the literature. These models exhibit fairly different features, make use of a diverse range of concepts, and show performance characteristics that vary significantly depending on the negotiation context. As a consequence, assessing and relating individual research contributions is a difficult task. Currently, there is a need to build a framework to define and characterize the essential features that are necessary to conduct automated negotiation and to compare the usage of key concepts in different publications. Furthermore, the development of such a framework can be an important step to identify the core elements of autonomous negotiating agents, to provide a coherent set of concepts related to automated negotiation, to assess progress in the field, and to highlight new research directions. Accordingly, this paper introduces a generic framework for automated negotiation. It describes, in detail, the components of the framework, assesses the sophistication of the majority of work in the AI literature on these components, and discusses a number of prominent models of negotiation. This paper also highlights some of the major challenges for future automated negotiation research.     

STRATUM: A METHODOLOGY FOR DESIGNING HEURISTIC AGENT NEGOTIATION STRATEGIES

Automated negotiation is a powerful (and sometimes essential) means for allocating resources among self-interested autonomous software agents. A key problem in building negotiating agents is the design of the negotiation strategy, which is used by an agent to decide its negotiation behavior. In complex domains, there is no single, obvious optimal strategy. This has led to much work on designing heuristic strategies, where agent designers usually rely on intuition and experience. In this article, we introduce STRATUM, a methodology for designing strategies for negotiating agents. The methodology provides a disciplined approach to analyzing the negotiation environment and designing strategies in light of agent capabilities and acts as a bridge between theoretical studies of automated negotiation and the software engineering of negotiation applications. We illustrate the application of the methodology by characterizing some strategies for the Trading Agent Competition and for argumentation-based negotiation.     

A risk management ontology for Quality-by-Design based on a new development approach according GAMP 5.0

A new approach to the development of a risk management ontology is presented. This method meets the requirements of a pharmaceutical Quality by Design approach, good manufacturing practice and good automated manufacturing practice. The need for a risk management ontology for a pharmaceutical environment is demonstrated, and the term “ontology” is generally defined and described with regard to the knowledge domain of quality risk management.To fulfill software development requirements defined by good manufacturing practice regulations and good automated manufacturing practice 5.0 for the novel development approach, we used a V-model as a process model, which is discussed in detail. The development steps for the new risk management ontology, such as requirement specification, conceptualization, formalization, implementation and validation approach, are elaborated.     

A Complex Networked Method of Sorting Negotiation Demand Based on Answer Set Programs

With the development of big data science, handling intensive knowledge in the complex network becomes more and more important. Knowledge representation of multi-agent negotiation in the complex network plays an important role in big data science. As a modern approach to declarative programming, answer set programming is widely applied in representing the multi-agent negotiation knowledge in recent years. But almost all the relevant negotiation models are based on complete rational agents, which make the negotiation process complex and low efficient. Sorting negotiation demands is the most key step in creating an efficient negotiation model to improve the negotiation ability of agents. Traditional sorting method is not suitable for the negotiation in the complex network. In this paper, we propose a complex networked negotiation, which can show the relationships among demands, and then a sorting method of negotiation demands is proposed based on demand relationships. What’s more, we use the betweenness of literals and the boundary co-efficient of rules to evaluate the importance of demands and rules.     

A Dialogue Game Protocol for Agent Purchase Negotiations

We propose a dialogue game protocol for purchase negotiation dialogues which identifies appropriate speech acts, defines constraints on their utterances, and specifies the different sub-tasks agents need to perform in order to engage in dialogues according to this protocol. Our formalism combines a dialogue game similar to those in the philosophy of argumentation with a model of rational consumer purchase decision behaviour adopted from marketing theory. In addition to the dialogue game protocol, we present a portfolio of decision mechanisms for the participating agents engaged in the dialogue and use these to provide our formalism with an operational semantics. We show that these decision mechanisms are sufficient to generate automated purchase decision dialogues between autonomous software agents interacting according to our proposed dialogue game protocol.     

A protocol for multi-agent negotiation in a group-choice decision making process

Negotiation is one of the most important features of agent interactions found in multi-agent systems, because it provides the basis for managing the expectations of the individual negotiating agents, and it enables selecting solutions that satisfy all the agents as much as possible. In order for negotiation to take place between two or more agents there is need for a negotiation protocol that defines the rules of the game; consequently, a variety of agent negotiation protocols have been proposed in literature. However, most of them are inappropriate for Group-Choice Decision Making (GCDM) because they do not explicitly exploit tradeoff to achieve social optimality, and their main focus is solving two-agent negotiation problems such as buyer–seller negotiation. In this paper we present an agent negotiation protocol that facilitates the solving of GCDM problems. The protocol is based on a hybrid of analytic and artificial intelligence techniques. The analytic component of the protocol utilizes a Game Theory model of an n-person general-sum game with complete information to determine the agreement options, while the knowledge-based (artificial intelligence) component of the protocol is similar to the strategic negotiation protocol. Moreover, this paper presents a tradeoff algorithm based on Qualitative Reasoning, which the agents employ to determine the ‘amount’ of tradeoff associated with various agreement options. Finally, the paper presents simulation results that illustrate the operational effectiveness of our agent negotiation protocol.     

A knowledge-based framework for complex, proactive and service-oriented e-negotiation systems

Advances in information technology and knowledge management change the way that e-negotiations, which constitute an important aspect of worldwide e-trading, can be structured and represented. In this paper, a novel approach that focuses on knowledge modeling, formalization, representation and management in the domain of e-negotiation is described. The proposed approach exploits Ontologies, Service Oriented Architectures, Semantic Web Services, software agent platforms, and Knowledge-Bases to construct a framework that favors dynamically adapted negotiation protocols, negotiation process visualization and management, modeling and preference elicitation of the negotiated object and automatic deployment of negotiation interfaces. Negotiation process, protocol and strategy are examined, and a hybrid approach that integrates rules and workflow diagrams to describe and represent them is introduced.     

Toward market-driven agents for electronic auction

While there are several existing agent-based systems addressing the crucial and difficult issues of automated negotiation and auction, this research has designed and engineered a society of trading agents with two distinguishing features: 1) a market-driven negotiation strategy and 2) a deal optimizing auction protocol. Unlike some of the existing systems where users manually select predefined trading strategies, in the market-driven approach, trading agents automatically select the appropriate strategies by examining the changing market situations. Results from a series of experiments suggest that the market-driven approach generally achieved more favorable outcomes as compared to the fixed strategy approach. Furthermore, it provides a more intuitive simulation of trading because trading agents are able to respond to different market situations with appropriate strategies. By augmenting the auction protocol with a deal optimization stage, trading agents can be programmed to optimize transaction deals by delaying the finalization of deals in search of better deals. Experimental results showed that by having a deal optimization stage, the auction protocol produced generally optimistic outcomes     

基于知识本体的协商Agents模型研究

知识本体具有知识共享,再利用和规则推理的能力,基于知识本体构建协商Agent模型,使协商Agent与特定的协商语言．协商协议和协商议题分离,解决异构Agent之间协商问题。     

基于知识本体的协商Agents模型研究

知识本体具有知识共享,再利用和规则推理的能力,基于知识本体构建协商Agent模型,使协商Agent与特定的协商语言,协商协议和协商议题分离,解决异构Agent之间协商问题。     

A learning-enabled infrastructure for electronic contracting agents

With the vigorous development of electronic commerce these years, many experts and scholars have devoted themselves to various fields of research and application. Of these fields, electronic contracting is a new research topic in great demand. In spite of its promise, electronic contracting involves the standardization of ontology and automation of negotiation, which renders the implementation of electronic contracting difficult. In view of the necessity of electronic contracting, we present a learning-enabled agent-based infrastructure and claim that it will be a solution to the problems encountered during the process of electronic contracting by a variety of evaluations. In this infrastructure, the applications of an agent are viewed as a set of application ontologies, each of which is a combination of a context ontology and a object ontology so that the negotiation context and automation of negotiation can be flexibly integrated in this infrastructure. The infrastructure enables the automation of electronic contracting through a general and automatic communication protocol and provides reusability by the componentization of agents. The infrastructure provides personalized multiattribute evaluation and proposal generation by a mechanism, which is a combination of neural networks and genetic algorithms, in order to enable the automatic negotiation ability at agents.     

Inter-agent cooperation and communication for agent-based robust dynamic scheduling in steel production

This paper describes a negotiation protocol proposed for inter-agent cooperation in a multi-agent system that we developed for optimisation and dynamic integrated scheduling within steel production. The negotiation protocol is a two-level bidding mechanism based on the Contract Net Protocol. The purpose of this protocol is to allow the agents to cooperate and coordinate their local schedules in order to find globally near-optimal robust schedules, whilst minimising the disruption caused by the occurrence of unexpected real-time events. We conduct several experiments to investigate the performance of this negotiation protocol to coordinate the agents in generating good quality robust schedules. This performance is evaluated in terms of stability and utility measures used to evaluate the robustness of the steel production processes in the presence of real-time events.     

An ontology-based approach to automated trust negotiation

We propose an ontology-based approach to automated trust negotiation (ATN) to establish a common vocabulary for ATN across heterogeneous domains and show how ontologies can be used to specify and implement ATN systems. The components of the ATN framework are expressed in terms of a shared ontology and ontology inference techniques are used to perform ATN policy compliance checking. On this basis, a semantically relevant negotiation strategy (SRNS) is proposed that ensures the success of a negotiation whenever it is semantically possible. We analyze the properties of SRNS and evaluate the performance of the ontology-based ATN.