Cooperative Distributed Problem Solving Research Articles

Disruption management in distributed enterprises: A multi-agent modelling and simulation of cooperative recovery behaviours

Disruption management in industrial areas consists in dealing with unanticipated events that get the plans deviate from their intended course. The solution results from the design and the maintenance of an operating mode ensuring a relevant deployment of individual recovery behaviours. The paper proposes an approach to minimize the impact of disrupting events on the whole system. It is based on an analysis of disrupting events and the characterization of the recovery process, and on a cooperative repair method for distributed industrial systems. This method is based on a cooperative distributed problem solving approach supported by a multi-agent system framework.

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.

Cooperative, hybrid agent architecture for real-time traffic signal control

This paper presents a new hybrid, synergistic approach in applying computational intelligence concepts to implement a cooperative, hierarchical, multiagent system for real-time traffic signal control of a complex traffic network. The large-scale traffic signal control problem is divided into various subproblems, and each subproblem is handled by an intelligent agent with a fuzzy neural decision-making module. The decisions made by lower-level agents are mediated by their respective higher-level agents. Through adopting a cooperative distributed problem solving approach, coordinated control by the agents is achieved. In order for the multiagent architecture to adapt itself continuously to the dynamically changing problem domain, a multistage online learning process for each agent is implemented involving reinforcement learning, learning rate and weight adjustment as well as dynamic update of fuzzy relations using an evolutionary algorithm. The test bed used for this research is a section of the Central Business District of Singapore. The performance of the proposed multiagent architecture is evaluated against the set of signal plans used by the current real-time adaptive traffic control system. The multiagent architecture produces significant improvements in the conditions of the traffic network, reducing the total mean delay by 40% and total vehicle stoppage time by 50%.

Domain Monotonicity and the Performance of Local Solutions Strategies for CDPS-based Distributed Sensor Interpretation and Distributed Diagnosis

The growth in computer networks has created the potential to harness a great deal of computing power, but new models of distributed computing are often required. Cooperative distributed problem solving (CDPS) is the subfield of multi-agent systems (MAS) that is concerned with how large-scale problems can be solved using a network of intelligent agents working together. Building CDPS systems for real-world applications is still very difficult, however, in large part because the effects that domain and strategy characteristics have on the performance of CDPS systems are not well understood. This paper reports on the first results from a new simulation-based analysis system that has been created to study the performance of CDPS-based distributed sensor interpretation (DSI) and distributed diagnosis (DD). To demonstrate the kind of results that can be obtained, we have investigated how the monotonicity of a domain affects the performance of a potentially very efficient class of strategies for CDPS-based DSI/DD. Local solutions strategies attempt to limit communications among the agents by focusing on using the agents' local solutions to produce global solutions. While these strategies have been described as being important for effective CDPS-based DSI/DD, they need not perform well if a domain is nonmonotonic. We had previously suggested that the reason they have performed well in several research systems was that many DSI/DD domains are what we termed nearly monotonic. In this paper, we will provide quantitative results that relate the performance of local solutions strategies to the monotonicity of a domain. The experiments confirm that domain monotonicity can be important to consider, but they also show that it is possible for these strategies to be effective even when domains are relatively nonmonotonic. What is required is that the agents receive a significant fraction of the data that is relevant to their subproblems. This has important implications for the design of DSI/DD systems using local solutions strategies. In addition, while the work indicates that many DSI/DD domains are likely to be “nearly monotonic” according to our original definitions, it also shows that these measures are not as predictive of performance as other measures we define. This means that near monotonicity alone does not explain why local solutions strategies have performed well in previous systems. Instead, a likely explanation is that these systems typically involved only a small number of agents.

Using the Concept of Intelligent Agents in FaultManagement of Distributed Services

This paper proposes the application of concepts from the area of intelligent agents to overcome deficiencies of existing management architectures regarding distribution of functionality and flexibility. Its main contribution is the proposal of a methodology for a flexible, distributed realization of complex management tasks. The main application areas are distributed services which are complex pieces of software, distributed across various heterogeneous end systems in a network. Mostly, they rely on the provision of other services as well. The approach relies on well-known concepts, such as cooperative distributed problem solving and intelligent agents, and offers a framework to combine these two concepts, providing a step on the roadmap to a flexible, distributed management architecture. The assessment of the approach is displayed throughout the paper by scenarios from the area of nontime critical fault management.

An object-oriented cooperative distributed problem solving shell with groupware management ability

In this paper, an Object-Oriented Cooperative Distributed Problem Solving Shell (OOCDPSS) with groupware management ability is designed. The groupware management facilities, which satisfy the needs of development and execution of the cooperative distributed problem solving activities, can reinforce concurrency and parallelism, accommodation and integration of heterogeneous, uncoordinated problem solvers cooperating on one common goal. This OOCDPSS system constructs the non-embedded groupware architecture by a hierarchy of leader agents. The leader agent that adopts a distributed blackboard control mechanism can assist the cooperating problem solvers with all the cooperative and coordinative activities at run time through a democratic, contract-net protocol. In this blackboard control mechanism, the system control unit and domain control unit are explicitly separated and put side-by-side in a simple control loop to simplify the control mechanism design. The event messages drive the above control units with the programmable heuristic knowledge, including the static knowledge, procedural knowledge, and strategic, situation-action behavior knowledge. In this OOCDPSS, a completely transparent environment and a programmable distributed blackboard control mechanism are provided. This environment automatically assists and supervises the progress of cooperative problem solving activities at run time, thereby raising the effective level of use among the preexisting problem solvers. In addition, by using the programmable heuristic knowledge, our approach can be efficiently implemented on the cooperative problem solving plans with a range of configurations. ©1997 John Wiley & Sons, Ltd.

An object‐oriented cooperative distributed problem solving shell with groupware management ability

In this paper, an Object-Oriented Cooperative Distributed Problem Solving Shell (OOCDPSS) with groupware management ability is designed. The groupware management facilities, which satisfy the needs of development and execution of the cooperative distributed problem solving activities, can reinforce concurrency and parallelism, accommodation and integration of heterogeneous, uncoordinated problem solvers cooperating on one common goal. This OOCDPSS system constructs the non-embedded groupware architecture by a hierarchy of leader agents. The leader agent that adopts a distributed blackboard control mechanism can assist the cooperating problem solvers with all the cooperative and coordinative activities at run time through a democratic, contract-net protocol. In this blackboard control mechanism, the system control unit and domain control unit are explicitly separated and put side-by-side in a simple control loop to simplify the control mechanism design. The event messages drive the above control units with the programmable heuristic knowledge, including the static knowledge, procedural knowledge, and strategic, situation-action behavior knowledge. In this OOCDPSS, a completely transparent environment and a programmable distributed blackboard control mechanism are provided. This environment automatically assists and supervises the progress of cooperative problem solving activities at run time, thereby raising the effective level of use among the preexisting problem solvers. In addition, by using the programmable heuristic knowledge, our approach can be efficiently implemented on the cooperative problem solving plans with a range of configurations. ©1997 John Wiley & Sons, Ltd.

An object-oriented method and language for implementing cooperative distributed problem solving

Cooperative distributed problem-solving systems (CDPS) offer computer methods for coordinating group expertise in the solving of problems. Much of the research to the present has been empirical testing of informal methods for implementation. There is a need for more formal methods to guide this process. Object-oriented methods provide a natural means of representing the essential features of CDPS in a formal, yet flexible, manner. Moreover, we can smoothly integrate object orientation and logic in a meaningful way, as demonstrated by the Harmony language. In this paper, we apply the Harmony framework to the field of CDPS. Our exposition takes the reader from conceptual development to fundamentals of an auditing application.

An active intelligent decision support system — Architecture and simulation

Development and implementation of decision support systems to support intelligent decision making is an area of research that has gained in importance in recent years. Due to the increased complexity of decision making, active involvement of the user and the computer in an intelligent way is necessary in the decision process. This paper presents issues in the design of an active intelligent decision support system (IDSS), develops an architectural model based on cooperative distributed problem solving, and performs a simulation of the system using object oriented programming for an example application in airfleet control.

Analyzing a quantitative coordination relationship

Coordination is a crucial behavior in cooperative distributed problem solving (CDPS). Analyzing coordination requires an understanding of the interplay between the agents, their problem, and their environment. The core behaviors ofdistributed coordination in CDPS systems are the coherent specification and scheduling of tasks over the set of distributed agents working on sets of interrelated problems. The complexity of, and uncertainty about, the problem interrelationships make distributed task coordination difficult. This article describes a causal model of this process that links the interrelationships, calledcoordination relationships, to the local scheduling constraints of distributed agents. Besides coordination relationships, environmental uncertainty and the lack of infinite computational resources also make distributed coordination difficult. It is not only the presence or absence of a coordination relationship that is important, but its quantitative properties: how likely is it to appear, how significant is its effect, and so on. These aspects determine the usefulness of a particular coordination relationship in the context defined by an environment, a problem to be solved, and an agent architecture. This article discusses the analysis of coordination relationships, using as an example our abstract model for thefacilitates relationship. We detail the derivation and assumptions of this model and apply it to the design of a generalized coordination module that is separate from, and interfaces cleanly with, the local scheduler of a CDPS agent. A set of simulation experiments is described that test our assumptions and design process in the coordination of a group of real-time problem-solving agents.

A GENERIC MODEL FOR INTELLIGENT NEGOTIATING AGENTS

Research in Cooperative Distributed Problem Solving (CDPS) considers how problem-solving tasks should be allocated among a group of agents and how the agents should coordinate their actions to achieve effective problem solving. For some CDPS systems, negotiation plays an important role in how agents cooperate. We define negotiation as the process of information exchange by which the agents act to resolve inconsistent views and to reach agreement on how they should work together in order to cooperate effectively. We describe a generic model, the Recursive Negotiation Model (RNM), that can serve as a basis for classifying and specifying where conflict resolution among multiple experts, viewpoints, or types of reasoning is needed in building a sophisticated CDPS system. This model defines where and how negotiation can be applied during problem solving based on structuring problem solving into four stages: problem formulation, focus-of-attention, allocation of goals or tasks to agents, and achievement of goals or tasks. We further discuss how the degree of agent participation in control decisions, including decisions about assigning responsibility to agents, influences the nature of negotiation within a particular system. Through this model, we emphasize that negotiation may be a recursive, complex, and pervasive process that is used to resolve conflicts in both domain-level and control-level problem solving. Finally, we survey existing negotiation frameworks and how they relate to our generic model.

Power system control using distributed and hierarchical problem solving

This paper proposes an expert system which is designed to relieve transmission line overloads in electric power systems using two kinds of heuristic approaches: cooperative distributed problem solving (CDPS) and hierarchical problem solving (HPS). CDPS is a problem-solving technique using distributed, divided and roughly connected knowledge bases. HPS uses hierarchically divided knowledge bases. Both techniques start with local problem solving in each knowledge base followed by the expansion of the problem-solving area by incorporating the knowledge bases. Abilities of three kinds of systems, namely CDPS, HPS and the conventional approach using centralized problem solving, are evaluated using the IEEE 30-bus test system and the New England 39-bus test system. As a result, the two-level hierarchical system is proved to be the most adequate for the New England 39-bus test system.

Knowledge-based support for management of concurrent, multidisciplinary design

Artificial intelligence (AI) applications to design have tended to focus on modeling and automating aspects of single discipline design tasks. Relatively little attention has thus far been devoted to representing the kinds of design ‘metaknowledge’ needed to manage the important interface issues that arise in concurrent design, that is, multidisciplinary design decision-making. This paper provides a view of the process and management of concurrent design and evaluates the potential of two AI approaches—blackboard architectures and co-operative distributed problem-solving (CDPS)—to model and support the concurrent design of complex artifacts. A discussion of the process of multidisciplinary design highlights elements of both sequential and concurrent design decision-making. We identify several kinds of design metaknowledge used by expert managers to: partition the design task for efficient execution by specialists; set appropriate levels of design conservatism for key subsystem specifications; evaluate, limit and selectively communicate design changes across discipline boundaries; and control the sequence and timing of the key (highly constrained and constraining) design decisions for a given type of artifact. We explore the extent to which blackboard and CDPS architectures can provide valid models of and potential decision support for concurrent design by (1) representing design management metaknowledge, and (2) using it to enhance both horizontal (interdisciplinary) and vertical (project life cycle) integration among product design, manufacturing and operations specialists.

AN ORGANIZATIONAL VIEW OF SYSTEMS PROBLEM SOLVING

The contribution of systems theory is reexamined from an organizational view. Its influence on artificial intelligence (and on computer science) is examined through the examples of analogical problem solving and cooperative distributed problem solving.

Cooperative distributed problem solving for communication network management

Much of previous Distributed Artificial Intelligence research has sought either to bring identical agents into closely coordinated groups, or to loosely coordinate the actions of dissimilar agents. The research described here explores close cooperation among heterogeneous agents, and is motivated by the requirements of a specific application in telecommunications network management: customer network control and joint private/public network management. In this domain, agents that manage the private and public networks must cooperate closely to provide satisfactory solutions to common network problems, yet they possess inherently distinct problem solving knowledge: private (or customer) networks are defined as logical networks constructed with the physical facilities provided by the public network. Thus, some of the network entities that define one agent's world knowledge are known by other agents at a different level of abstraction, creating a complex interdependence among agent problem solving activities. This paper provides some basic motivation for cooperative distributed problem solving and its application to communication network management in general, and reports on efforts to understand the nature of cooperation and the functionality of agents in the customer network control domain. In the process, the paper describes a three-agent facility failure problem and an associated interagent cooperation scenario, and presents a research testbed, TEAM-CPS, that explores cooperative problem solving and multiagent interaction.

Trends in cooperative distributed problem solving

The authors present an overview of cooperative distributed problem solving (CDPS), an emerging research area that combines aspects of AI (artificial intelligence) and distributed processing. CDPS can be used to study how a loosely coupled network of sophisticated problem-solving nodes can solve a complex problem which consists of a set of interdependent subproblems. Subproblems arise because of spatial, temporal, and functional distribution of data, knowledge, and processing capabilities. Application areas include distributed interpretation, distributed planning and control, cooperating expert systems, and computer-supported human cooperation. The authors survey the important approaches and empirical investigations that have been developed. The approaches covered include negotiation, functionally accurate cooperation, organizational structuring, multiagent planning, sophisticated local control, and theoretical frameworks.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

The Distributed Vehicle Monitoring Testbed: A Tool for Investigating Distributed Problem Solving Networks

Cooperative distributed problem solving networks are distributed networks of semi-autonomous processing nodes that work together to solve a single problem. The Distributed Vehicle Monitoring Testbed is a flexible and fully-instrumented research tool for empirically evaluating alternative designs for these networks. The testbed simulates a class of a distributed knowledge-based problem solving systems operating on an abstracted version of a vehicle monitoring task. There are two important aspects to the testbed: (1.) it implements a novel generic architecture for distributed problems solving networks that exploits the use of sophisticated local node control and meta-level control to improve global coherence in network problem solving; (2.) it serves as an example of how a testbed can be engineered to permit the empirical exploration of design issues in knowledge AI systems. The testbed is capable of simulating different degrees of sophistication in problem solving knowledge and focus-of attention mechanisms, for varying the distribution and characteristics of error in its (simulated) input data, and for measuring the progress of problem solving. Node configuration and communication channel characteristics can also be independently varied in the simulated network.