多agent系统中agent的行为决策

1.介绍 agent是指在某一环境下能够持续自主运行,具有社会性、反应性、自发性等特征的计算实体。多agent系统由一组具有一定资源和能力、相对独立且交互合作的agent组成。由于多agent系统提供了更高层次的抽象模型,能够自然、贴切、直观地表示现实世界中的计算实体及其问题求解方     

基于多Agent的动态路径规划方法研究

简要地介绍了多Agent技术,并以城市交通诱导系统中的动态路径规划为研究对象,提出了一种基于范例推理合同网协商机制的多Agent动态路径规划方法。     

多agent智能制造系统中通信机制的研究

在分析agent和多agent系统的特点的基础上，着重研究了基于多agent的智能制造系统中的通信问题，提出了对话模式作为agent之间的通信机制，并使用着色Petri网进行了校验。     

多agent规划领域中的观察信息约简

观察信息约减是近年来不确定规划中的研究热点,但研究集中于单个agent的环境,在多agent规划环境下的研究不足。面对多agent环境下的规划问题,设计了一种用于不确定规划领域中多agent求解协同规划解的ORMAP算法。该算法首先根据基于模型检测的不定规划中的状态分层思想,将问题领域的所有状态进行分层,以此来减少不同的agent的冲突,再利用以最小代价优先的回溯法搜索协同规划解,同时在解的搜索过程中选择最小的观察信息集,使求出的协同规划解在众多符合条件的协同规划解中所需要的观察信息最少或接近最少,这样就达到了信息约简的目的。最后通过实验证明,在考虑了观察信息约简的限制条件后,这种算法的效率较高。     

通用规划综述*

对智能规划中的通用规划思想及方法进行了全面综述。通用规划是对特定的规划领域制定通用的解形式,从而可以不通过搜索而直接得到具体规划问题的解。当搜索空间随着问题规模指数级增长时,人们希望通过归纳已有规划解的规律,以较小的代价来获取大规模问题的解。介绍了通用规划的基本思想和产生方法,讨论了其与相关工作的联系以及局限性,并给出了对其未来研究方向的展望。     

智能Agent与多Agent系统的研究

智能Agent及多Agent系统自20世纪80年代起一直是分布式人工智能研究的热点。对Agent理论，语言，结构以及多Agent系统结构等问题进行了研究，并对Agent与对象（Object) ,过程控制系统，软件“精灵”以及多Agent系统与分布式问题求解的区别进行了分析。     

多agent在网络智能答疑系统上的应用

随着互联网技术的出现和发展,网络答疑系统也得到了广泛的应用并且取得了较好的教育效果.然而一般网络答疑系统存在智能化程度低,交互性差的问题.智能网络答疑系统是一种以先进的Agent理论为技术基础的答疑系统,具有智能化程度高、交互性高的优势.该文阐述了基于Agent的网络智能答疑系统的构建思路和设计流程.     

用遗传算法实现多移动机器人安全路径规划

针对动态环境中多移动机器人路径规划问题提出了一种遗传算法.该算法的适应值与间隙呈线性关系,计算简单,将协调路径适应值矩阵引入遗传算法,实现了多移动机器人安全路径规划.仿真结果验证了该算法在多移动机器人路径规划中的可行性和有效性.     

多Agent技术综述

多Agent系统(MAS)是分布式人工智能(DAI)的主要研究方向之一,提出了MAS的概念,对MAS的研究基础进行了介绍,阐述了三种典型的MAS体系结构,对MAS中的规划进行了介绍和具体分类.并介绍了MAS技术的典型应用.最后,对MAS技术进行了总结与展望.     

多Agent Teamwork研究综述

Teamwork在许多动态、复杂的多Agent环境中占据越来越重要的地位，是目前人工智能界研究的热点之一，通过对多Agent Teamwork的研究现状、关键技术和发展趋势进行综述和讨论，试图勾画出目前Teamwork研究的脉络、重点及其发展趋向。主要内容包括：（1）Teamwork研究的背景；（2）Teamwork的研究方法以及典型的Teamwork模型；（3）Teamwork模型的特点以及关键技术；（4）Teamwork的应用领域以及进一步研究的方向。     

A privacy-preserving model for multi-agent propositional planning

Abstract

Over the last years, the planning community has formalised several models and approaches to multi-agent (MA) propositional planning. One of the main motivations in MA planning is that some or all agents have private knowledge that cannot be communicated to other agents during the planning process and the plan execution. We argue that the existing models of the multi-agent planning task do not maintain the agents’ privacy when a (strict) subset of the involved agents share confidential knowledge, or when the identity/existence of at least one agent is confidential. In this paper, first we propose a model of the MA-planning tasks that preserves the privacy of the involved agents when this happens. Then we investigate an algorithm based on best first search for our model that uses some new heuristics providing a trade-off between accuracy and agents’ privacy. Finally, an experimental study compares the effectiveness of using the proposed heuristics.     

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.     

基于多代理的供应链协同生产计划模型

供应链是由分布在全球的供应商、制造商、仓库、分销中心和零售商组成的复杂网络。其生产计划具有分布性,自治性,同步性和开放性等特点,使得传统的生产计划方法已经不能适应供应链的计划需求。在分析了多代理技术和供应链系统生产计划特点的基础上,采用智能代理封供应链系统的功能实体和物理实体进行封装,提出了一个基于多代理的供应链系统网络模型,并构建了基于多智能代理的生产计划运行模式。该生产计划模型分为三层：全局生产计划,企业内部子生产计划和各个任务的详细生产计划。它突破了传统生产计划的局限性,从全局规划的角度来整合供应链上的所有资源,消除了不同企业子生产计划所产生的冲突和差异。很好的体现了供应链系统信息共享和资源共享的原则。     

A multi-agent based agile manufacturing planning and control system

In today’s manufacturing enterprise, the performance of customer service level (e.g., short ordering-to-delivery time, low price) is highly dependent on the effectiveness of its manufacturing planning and control system (MPCS). However, most of the current MPCS, employed the hierarchical planning approach, may have some drawbacks, such as structural rigidity, difficulty of designing a control system, and lack of flexibility. Currently, RFID (Radio Frequency Identification) technology has been applied to enhance the visibility, accountability, track ability and traceability of manufacturing system whenever the accurate and detailed manufacturing information (e.g., raw material, WIP, products in factory and products in the down streams) of products will be followed in real-time basis by RFID technique. In addition, a multi-agent approach may be applied in a distributed and autonomous system which allows negotiation-based decision making. Therefore, the objective of this research is to study the application of RFID technique and multi-agent system (MAS) in developing an agent-based agile manufacturing planning and control system (AMPCS) to respond to the dynamically changing manufacturing activities and exceptions.In AMPCS, RFID-based manufacturing control (R-MC) module plays the role of controlling the manufacturing system in which production items and manufacturing resources attached with RFID tag may actively feedback production status to and receive production and operations schedule from advanced manufacturing planning (AMP) module. In addition, a bidding process and algorithm is developed to generate operations schedule by using the characteristics of MAS. Performance analysis (PA) module is responsible not only for evaluating the scheduling results but also for evaluating the performance of production execution. The development of an AMPCS for an automated manufacturing cell demonstrates that the integration of RFID technique and MAS in developing an agile manufacturing planning and control system can really possess the characteristics of visibility, accountability, track ability, responsiveness, and flexibility in a distributed and dynamic manufacturing system.     

Integrate multi-agent planning in hinterland transport: Design,implementation and evaluation

This paper addresses the planning issue in hinterland barge transport domain, characterized by limited information sharing, lack of cooperation and conflict of interest among different parties (terminal and barge party). The planning problem is formulated as a novel Stackelberg game to model a leader–followers bi-level optimization problem. A hybrid algorithm is developed that concerns different objectives (vessel turn around and terminal berthing capacity) simultaneously while fulling pre-defined operational constraints. The presented algorithm is outlined in a hierarchical way and embedded into dedicated agents as decision-making kernel. We describe the architecture and the implementation of the proposed mediator-based multi agent system and overall coupling framework include agent identification, coordination and decision making. A case study evaluates the performance of our approach in terms of global optimality compared with other related approach.     

An innovative multi-agent search-and-rescue path planning approach

Search and rescue path planning is known to be computationally hard, and most techniques developed to solve practical size problems have been unsuccessful to estimate an optimality gap. A mixed-integer linear programming (MIP) formulation is proposed to optimally solve the multi-agent discrete search and rescue (SAR) path planning problem, maximizing cumulative probability of success in detecting a target. It extends a single agent decision model to a multi-agent setting capturing anticipated feedback information resulting from possible observation outcomes during projected path execution while expanding possible agent actions to all possible neighboring move directions, considerably augmenting computational complexity. A network representation is further exploited to alleviate problem modeling, constraint specification, and speed-up computation. The proposed MIP approach uses CPLEX problem-solving technology in promptly providing near-optimal solutions for realistic problems, while offering a robust upper bound derived from Lagrangean integrality constraint relaxation. Modeling extension to a closed-loop environment to incorporate real-time action outcomes over a receding time horizon can even be envisioned given acceptable run-time performance. A generalized parameter-driven objective function is then proposed and discussed to suitably define a variety of user-defined objectives. Computational results reporting the performance of the approach clearly show its value.     

Finite-time multi-agent deployment: A nonlinear PDE motion planning approach

The systematic flatness-based motion planning using formal power series and suitable summability methods is considered for the finite-time deployment of multi-agent systems into planar formation profiles along predefined spatial–temporal paths. Thereby, a distributed-parameter setting is proposed, where the collective leader–follower agent dynamics is modeled by two boundary controlled nonlinear time-varying PDEs governing the motion of an agent continuum in the plane. The discretization of the PDE model directly induces a decentralized communication and interconnection structure for the multi-agent system, which is required to achieve the desired spatial–temporal paths and deployment formations.     

基于MAS技术的多星协同侦察任务规划系统设计*

基于MAS技术,提出用多agent系统来实现多星协同侦察任务规划系统,建立系统的总体结构,并对其中的关键技术进行分析,给出了基于合同网的多星协作结构,实现了侦察任务分解和任务分配;在单个agent中利用已有规划器SAPA实现单星行动规划。基于MAS建立的任务规划系统具有较好的智能性和自主性。     

A multi-agent architecture for outsourcing SMEs manufacturing supply chain

In the present, global and competitive market customer's demands are very volatile. It is very difficult for small and medium size enterprises (SMEs) to satisfy their customer with quality product in reasonable price. Large firms are spending huge amount of their budget in generating technology development. To cope with this competitive market, usually, SMEs concentrate on their core expertise and outsource some non-core items or activities. The outsourcing decision (when, what, whom) is very crucial for small-scale industries. Realizing this scenario, in this article, an automated self-adaptive multi-agent system has been proposed. The proposed system will help SMEs to take an appropriate decision to mitigate the uncertainty in supply chain. The developed system exploits the “Outsourcing of operations” feature by its agents to conclude the manufacturing processes faster and reduce the idle time of certain machines with less human intervention. The communication protocol for agents has been described to give an insight of their communication. It was explained how various agents like outsourcing, material planning and supplier selection will come into action at different stages and take appropriate outsourcing decisions. Therefore, this multi-agent architecture will facilitate small scale manufacturing industries to execute their manufacturing processes and complex logistics issues efficiently. The execution of proposed architecture has been described in the simulated case study.     

多智能体系统分布式一致性算法研究现状

综述了多智能体系统分布式一致性问题的研究现状。从理论层面介绍了一致性问题的几种常见定义及与特性相关的主要参数;总结归纳了近年来几种一致性协议及其理论分析结果;分析和阐述了一致性问题的主要应用领域的进展。展望了未来的研究方向。