A distributed problem-solving approach to collaborative facility engineering

A framework for collaborative facility engineering is presented. The framework is based on a distributed problem-solving approach to collaborative facility engineering and employs an integration approach called Agent-Based Software Engineering as an implementation vehicle of this approach. The focal entity of this framework is a Multiagent Design Team (MDT) that comprises a collection of software agents (e.g. design software applications with a certain standard communication interface) and a design specialist, which together perform specific design tasks. Multiagent design teams are autonomous and form an organizational structure based on a federation architecture. Every multiagent design team surrenders its autonomy to a system program called facilitator, which coordinates the interaction among software agents in the federation architecture. Facilitators can be viewed as representatives of one or more teams that facilitate the exchange of design information and knowledge in support of the design tasks they perform. In the federation architecture, design specialists collaborate by exchanging design information with others via their software agents, and by identifying and resolving design conflicts by negotiation. In addition to a discussion of the framework's primary components, its realization in an integrated distributed environment for collaborative building engineering is described.     

Developing cooperation mechanism for multi-agent systems with Petri nets

Although the contract net protocol answers some of the questions in cooperative distributed problem solving (CDPS), it raises many others that CDPS researchers are still trying to answer. In contract net protocol, an agent may play the role of a manager or a bidder. Without a coordination mechanism, a manager may acquire excessive resources from the bidders in forming a collaborative network to execute the assigned task and thus hinder the progress of the tasks assigned to other managers due to resource contention. As a result, application of contract net protocol may not always lead to feasible solutions to accomplish tasks effectively. As a general framework for exchanging messages, the original contract net protocol does not prescribe how agents should cooperate. How to develop a collaborative mechanism to effectively perform the tasks is an important issue. This paper aims to improve the insufficiency of the contract net by developing a mechanism to facilitate cooperation of agents to accomplish their tasks while avoiding undesirable states and enhance the overall system performance in manufacturing systems. To achieve these objectives, detail process models about how agents accomplish their tasks are required. Due to the advantages in modeling concurrent, synchronous and/or asynchronous activities, Petri nets are adopted in this paper. Based on Petri net models, we study the information needed for agents to make cooperative decisions, mechanism to make agents cooperate, and how to enhance the performance in the system level by taking advantage of the agents’ cooperation capabilities. To characterize the condition for cooperation, we represent the collaborative networks formed based on the contract net protocol with Petri nets and then find the condition for a collaborative network to be feasible. The feasible condition also serves as a condition for the development of cooperation mechanism for managers. We propose a cooperation mechanism based on the idea of resource donation, including unilateral resource donation and reciprocal resource donation. Implementation architecture has also been proposed to realize our methodology.     

一种基于智能体技术的软件自适应动态演化机制

针对分布式软件系统在动态演化中面临的原有软件单元难以重用、忽视软件内部运行状态引发的演化需求等问题,借助智能体(agent)具有的环境适应性、变化敏感性等特征,提出了一种基于智能体技术的软件自适应动态演化机制.通过将软件单元封装为Agent,并定义单元间的演化规则,使演化机制重用原有软件单元.通过一种基于数据推送的动态环境感知方法实现Agent间协作关系调整,同时满足来自内外部环境引发的动态演化需求.通过引入信息中介服务,实现了基于改进合同网的Agent协作策略,能够自适应地更替Agent,满足用户意愿变更引发的动态演化需求.依据演化机制在支撑环境中的运行情况及相关能力指标的分析,说明所提出的演化机制适用于动态复杂的分布式软件系统,是一种有效的软件自适应动态演化机制.     

Collaborative real-time traffic information generation and sharing framework for the intelligent transportation system

Real-time traffic information collection and data fusion is one of the most important tasks in the advanced traffic management system (ATMS), and sharing traffic information to users is an essential part of the advance traveler information system (ATIS) among the intelligent transportation systems (ITS). Traditionally, sensor-based schemes or probing-vehicle based schemes have been used for collecting traffic information, but the coverage, cost, and real-time issues have remained unsolved. In this paper, a wiki-like collaborative real-time traffic information collection, fusion and sharing framework is proposed, which includes user-centric traffic event reacting mechanism, and automatic agent-centric traffic information aggregating scheme. Smart traffic agents (STA) developed for various front-end devices have the location-aware two-way real-time traffic exchange capability, and built-in event-reporting mechanism to allow users to report the real-time traffic events around their locations. In addition to collecting traffic information, the framework also integrates heterogeneous external real-time traffic information data sources and internal historical traffic information database to predict real-time traffic status by knowledge base system technique.     

Collaborative intelligent CAD framework incorporating design history tracking algorithm

This paper shows a new and efficient collaborative intelligent Computer Aided Design (CAD) framework in a theoretical study. While other collaborative CAD frameworks or protocols focus on decreasing the waiting time for updating design or communication methods for design review among collaborative designers, the suggested collaborative design protocol determines the next design ownership criterion with the objective of minimizing redundant design stages and design bottlenecks using the design history. In addition, the suggested framework generates an efficient reverse-engineered process for achieving the final design target with identification of redundant designs and how these can be prevented while resolving other existing collaborative design issues. As a design history mechanism, a feature-based design history tracking algorithm is suggested. In each design stage, the modeling activities are mapped to the related geometry and topology information. This information is reasoned into features using the feature design history graph (FDHG) and modified attribute adjacency graph (MAAG). The identified features are utilized for determining the redundant design stage and how it can be changed efficiently using the tracking algorithm. As the size of the design history increases with the number of collaborative designers and their design stages, this design history mechanism contributes to a decrease in size and captures the characteristics of design using features. As possible directions for future research this suggested framework can provide an insight into the design tendencies of designers and also be used as a reference model for intelligent CAD systems with an extracted design history-based knowledge database.     

Collaborative contracting for Manufacturing-as-a-Service (MaaS) by information content measurement and decision tree learning

Product realization through Manufacturing-as-a-Service (MaaS) has observed as an emerging trend towards Industry 4.0. It offers new opportunities for reaching external partner’s knowledge and resources while allowing companies to focus on their core competencies. This paper envisions the importance of collaborative contracting for MaaS fulfillments, in which tournament-based crowdsourcing entails evaluation and selection of manufacturing service providers as a best-matching problem of multi-criteria decision making. MaaS collaborative contracting involves numerous evaluation criteria related to not only technical capabilities of the fulfilling agents, but also their business performance involved with MaaS operations in the past history. This paper develops a contracting analysis and evaluation methodology for selection of appropriate MaaS agent selection. The proposed evaluation mechanism utilizes information content measure and decision tree learning for better matching of fulfilling agents to maximize customer satisfaction and effectiveness of multiple stakeholders of MaaS operations. The multi-attribute utility theory is integrated with decision tree learning within a coherent predictive analytics framework to not only synthesize pre-defined functional and cost requirements for customers, but also leverage upon historical data of business performance. A case study of orthodontic brace mass customization through MaaS is reported to illustrate the feasibility and potential of collaborative contracting in MaaS.     

Development of a collaborative virtual maintenance environment with agent technology

This paper proposed a virtual environment with agent technology to facilitate the integration and cooperation of product maintenance process. The agent-based system framework, in which various intelligent agents worked together to perform product maintenance tasks in an autonomous and collaborative way, is addressed. The functional definition of each intelligent agent is presented and the agent internal structure is designed. Moreover, ontology-based agents communication mechanism and agents co-operation model are proposed, and an intelligent algorithm based on fuzzy comprehensive evaluation is designed to solve competition conflicts among the agents. Finally, the prototype system is developed and the algorithm is proved feasible and efficient.     

Using agents to enable collaborative work

With the commercialization of the Web, you can find the information you need, but you may also find an applet or CGI bin ready to charge you for it. In what was originally a cooperative environment where discovering and copying information were free, interactions (and the agents involved) are now acquiring an economic basis. We consider how the introduction of agents and, more specifically, agents whose interactions have an economic basis can actually lead to a new dimension for developing systems for computer supported cooperative work. Until recently, the gap between agent technology and the technology available for CSCW appeared to preclude much interaction between the two communities. However, agent based mechanisms have become sophisticated enough to be used by collaborative systems to perform task allocation, scheduling, triggering, and other low-level functions. The methods for entering into collaborative agreements now seem promising     

Design and implementation of an agent-based collaborative product design system

The evolution of computer science and technology has brought new opportunities for multidisciplinary designers and engineers to collaborate with each other in a concurrent and coordinated manner. The development of computational agents with unified data structures and software protocols contributes to the establishment of a new way of working in collaborative design, which is increasingly becoming an international practice. In this paper, based on the analysis of the dynamic nature of collaborative design process, a new framework for collaborative design is described. This framework adopts an agent-based approach and relocates designers, managers, systems, and the supporting agents in a unified knowledge representation scheme for product design. In order to model the constantly evolving design process and the rationales resulted from design collaboration, a Collaborative Product Data Model (CPDM) and a constraint-based Collaborative Design Process Model (CDPM) are proposed to facilitate the management and coordination of the collaborative design process as well as design knowledge management. A prototype system of the proposed framework is implemented and its feasibility is evaluated using a real design scenario whose objective is designing a set of dining table and chairs.     

An intelligent agent-based collaborative information security framework

In this paper we proposed a framework for collaborative intelligent agents in a distributed environment to execute sound security strategies for protecting information resources. First, the intelligent agent-based Duty Reliable Center (DRC) in the model uses the group decision method to determine a global information threat level. With the threat level, local agent employs the Bayes’ decision procedure to calculate the expected loss of its all-possible actions, and then chooses an action among them with the minimum expected loss to protect its information resources. The proposed framework enables an agent to choose among alternatives in an optimal fashion, taking into account the worth of acquiring prior information to reduce uncertainty. Because system operations are distributed, hackers are unlikely to wreck the whole system. Thus, it is expected to yield information security cost-effective solutions.     

A knowledge intensive multi-agent framework for cooperative/collaborative design modeling and decision support of assemblies

Multi-agent modeling has emerged as a promising discipline for dealing with decision making process in distributed information system applications. One of such applications is the modeling of distributed design or manufacturing processes which can link up various designs or manufacturing processes to form a virtual consortium on a global basis. This paper proposes a novel knowledge intensive multi-agent cooperative/collaborative framework for concurrent intelligent design and assembly planning, which integrates product design, design for assembly, assembly planning, assembly system design, and assembly simulation subjected to econo-technical evaluations. An AI protocol based method is proposed to facilitate the integration of intelligent agents for assembly design, planning, evaluation and simulation process. A unified class of knowledge intensive Petri nets is defined using the O-O knowledge-based Petri net approach and used as an AI protocol for handling both the integration and the negotiation problems among multi-agents. The detailed cooperative/collaborative mechanism and algorithms are given based on the knowledge objects cooperation formalisms. As such, the assembly-oriented design system can easily be implemented under the multi-agent-based knowledge-intensive Petri net framework with concurrent integration of multiple cooperative knowledge sources and software. Thus, product design and assembly planning can be carried out simultaneously and intelligently in an entirely computer-aided concurrent design and assembly planning system.     

Mobile-agent-based collaborative sensor fusion

Information fusion can assist in the development of sensor network applications by merging capabilities, raw data and decisions from multiple sensors through distributed and collaborative integration algorithms. In this paper, we introduce a multi-layered, middleware-driven, multi-agent, interoperable architecture for distributed sensor networks that bridges the gap between the programmable application layer consisting of software agents and the physical layer consisting of sensor nodes. We adopt an energy-efficient, fault-tolerant approach for collaborative information processing among multiple sensor nodes using a mobile-agent-based computing model. In this model the sink/base-station deploys mobile agents that migrate from node to node following a certain itinerary, either pre-determined or determined on-the-fly, and fuse the information/data locally at each node. This way, the intelligence is distributed throughout the network edge and communication cost is reduced to make the sensor network energy-efficient. We evaluate the performance of our mobile-agent-based approach as well as that of the traditional client/server-based computing model, vis-à-vis energy consumption and execution time, through both analytical study and simulation. We draw important conclusions based on our findings. Finally, we consider a collaborative target classification application, supported by our architectural framework, to illustrate the efficacy of the mobile-agent-based computing model.     

ResIoT: An IoT Social Framework Resilient to Malicious Activities

The purpose of the next internet of things (IoT) is that of making available myriad of services to people by high sensing intelligent devices capable of reasoning and real time acting. The convergence of IoT and multi-agent systems (MAS) provides the opportunity to benefit from the social attitude of agents in order to perform machine-to-machine (M2M) coopera-tion among smart entities. However, the selection of reliable partners for cooperation represents a hard task in a mobile and federated context, especially because the trustworthiness of devices is largely unreferenced. The issues discussed above can be synthesized by recalling the well known concept of social resilience in IoT systems, i.e., the capability of an IoT network to resist to possible attacks by malicious agent that potentially could infect large areas of the network, spamming unreliable infor-mation and/or assuming unfair behaviors. In this sense, social resilience is devoted to face malicious activities of software agents in their social interactions, and do not deal with the correct working of the sensors and other information devices. In this setting, the use of a reputation model can be a practicable and effective solution to form local communities of agents on the basis of their social capabilities. In this paper, we propose a framework for agents operating in an IoT environment, called ResIoT, where the formation of communities for collaborative purposes is performed on the basis of agent reputation. In order to validate our approach, we performed an experimental campaign by means of a simulated framework, which allowed us to verify that, by our approach, devices have not any economic convenience to performs misleading behaviors. Moreover, further experimental results have shown that our approach is able to detect the nature of the active agents in the systems (i.e., honest and malicious), with an accuracy of not less than 11% compared to the best competitor tested and highlighting a high resilience with respect to some malicious activities.      

Agent组织中的政策导向型协作模型

传统Agent协作模型强调Agent的高度自主性,其自发协作过程完全出于内部的"自私性"动机,难以在模型中表达宏观层面上的引导及系统外部的约束,在应用于开放复杂软件系统时,将面临可信度不能满足要求、计算复杂度高及没有有效的冲突消解机制这3方面的问题,这阻碍了Agent技术在现实软件系统建模中的应用.采用组织与政策隐喻,提出Agent组织中的政策导向型协作模型,通过组织与政策给予Agent以宏观上的引导与外部的控制,以增强系统的可信度;采用扩展的可废止逻辑框架,对这一协作过程建立一个具有线性计算复杂度的形式化理论;逻辑体系中内置的优先级方式为系统提供了有效的冲突消解机制.并证明了模型所具有的一致性及其他特性,最后通过一个实例对系统作出验证性说明.     

Incentive compatible regression learning

We initiate the study of incentives in a general machine learning framework. We focus on a game-theoretic regression learning setting where private information is elicited from multiple agents with different, possibly conflicting, views on how to label the points of an input space. This conflict potentially gives rise to untruthfulness on the part of the agents. In the restricted but important case when every agent cares about a single point, and under mild assumptions, we show that agents are motivated to tell the truth. In a more general setting, we study the power and limitations of mechanisms without payments. We finally establish that, in the general setting, the VCG mechanism goes a long way in guaranteeing truthfulness and economic efficiency.     

CCM‐SLAM: Robust and efficient centralized collaborative monocular simultaneous localization and mapping for robotic teams

Robotic collaboration promises increased robustness and efficiency of missions with great potential in applications, such as search‐and‐rescue and agriculture. Multiagent collaborative simultaneous localization and mapping (SLAM) is right at the core of enabling collaboration, such that each agent can colocalize in and build a map of the workspace. The key challenges at the heart of this problem, however, lie with robust communication, efficient data management, and effective sharing of information among the agents. To this end, here we present CCM‐SLAM, a centralized collaborative SLAM framework for robotic agents, each equipped with a monocular camera, a communication unit, and a small processing board. With each agent able to run visual odometry onboard, CCM‐SLAM ensures their autonomy as individuals, while a central server with potentially bigger computational capacity enables their collaboration by collecting all their experiences, merging and optimizing their maps, or disseminating information back to them, where appropriate. An in‐depth analysis on benchmarking datasets addresses the scalability and the robustness of CCM‐SLAM to information loss and communication delays commonly occurring during real missions. This reveals that in the worst case of communication loss, collaboration is affected, but not the autonomy of the agents. Finally, the practicality of the proposed framework is demonstrated with real flights of three small aircraft equipped with different sensors and computational capabilities onboard and a standard laptop as the server, collaboratively estimating their poses and the scene on the fly.     

Agent-based framework for integrated facility engineering

An agent-based framework for the development of integrated facility engineering environments in support of collaborative design is introduced. This framework aims at integrating design software by allowing better software interoperability. Within their framework, design agents represent various existing design and planning systems that communicate their design information and knowledge partially and incrementally using the Agent Communication Language (ACL). ACL is a formal language proposed as a communication standard for disparate software. It is based on a logic-based language called Knowledge Interchange Format (KIF) and a message protocol called Knowledge Query Manipulation Language (KQML). Design agents are linked and their communication of design information is coordinated via system programs called facilitators in a federation architecture. The federation architecture specifies the way design agents and facilitators communicate in an integrated software environment. In concert with pursuing fundamental research concepts, we have been developing an integrated design software environment that spans different phases of the facility life cycle. This environment serves to demonstrate the primary aspects of this research methodology. In this paper, we first discuss the integration problem and review related research projects. We then present the major aspects of agent-based software engineering methodology and its application to integrated facility engineering. A highlight of the current integrated design environment development is given to illustrate the advantages of this approach. Finally, we summarize and discuss some of the important research issues in light of previous research.     

An adaptive framework for monitoring agent organizations

Multiagent technologies are usually considered to be suitable for constructing agent organizations that are capable of running in dynamic and distributed environments and that are able to adapt to changes as the system runs. The necessary condition for this adaptation ability is to make agents aware of significant changes in both the environment and the organization. This paper presents mechanism, which helps agents detecting adaptation requirements dynamically at run time, and an Trace&Trigger, which is an adaptation framework for agent organizations. It consists of an event-tracing-based monitoring mechanism that provides organizational agents with information related to the costs and benefits of carrying out an adaptation process at each moment of the execution. This framework intends to overcome some of the problems that are present in other approaches by allowing the dynamic specification of the information that has to be retrieved by each agent at each moment for adaptation deliberation, avoiding the transference of useless information for adaptation deliberation. This framework has been integrated in the Magentix2 multiagent platform. In order to test its performance benefits for any agent organization, an example based on a market scenario is also presented.     

A user requirement driven framework for collaborative design knowledge management

In today’s competitive global marketplace and knowledge-based economy, user requirement becomes an important input information for enterprises to develop new product and a critical factor to drive product collaborative design evolution. Meanwhile, there remains no consensus on how best to support knowledge activities and significant challenges to establishing design information management facing to rapid collaborative product development with dynamic user requirement. This paper introduces solutions for designer to deal with dynamic user requirement information through requirement evaluation and prediction method. In this study, we propose a user requirements-oriented knowledge management concept that is based on a four level hierarchy map model with special regard to knowledge collaboration and information communication. Furthermore, a novel distributed concurrent and interactive user requirement database was constructed, and the framework driven by user requirement was put forward to support collaborative design knowledge management. Finally, the service robot design project of a start-up company is used as a case study to explain the implementation of proposed framework.     

A framework using cluster-based hybrid network architecture for collaborative virtual surgery

Research on collaborative virtual environments (CVEs) opens the opportunity for simulating the cooperative work in surgical operations. It is however a challenging task to implement a high performance collaborative surgical simulation system because of the difficulty in maintaining state consistency with minimum network latencies, especially when sophisticated deformable models and haptics are involved. In this paper, an integrated framework using cluster-based hybrid network architecture is proposed to support collaborative virtual surgery. Multicast transmission is employed to transmit updated information among participants in order to reduce network latencies, while system consistency is maintained by an administrative server. Reliable multicast is implemented using distributed message acknowledgment based on cluster cooperation and sliding window technique. The robustness of the framework is guaranteed by the failure detection chain which enables smooth transition when participants join and leave the collaboration, including normal and involuntary leaving. Communication overhead is further reduced by implementing a number of management approaches such as computational policies and collaborative mechanisms. The feasibility of the proposed framework is demonstrated by successfully extending an existing standalone orthopedic surgery trainer into a collaborative simulation system. A series of experiments have been conducted to evaluate the system performance. The results demonstrate that the proposed framework is capable of supporting collaborative surgical simulation.