Trends in cooperative distributed problem solving
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Cooperative Distributed Problem Solving for Communication Network Management
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- Robert Weihmayer 2 &
- Richard Brandau 2
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Much of previous Distributed Artificial Intelligence (DAI) 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 the other agents at a different level of abstraction, creating a complex interdependence between 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 (Testbed Environment for Autonomous Multiagent Cooperative Problem Solving), that explores cooperative problem solving and multiagent interaction.
Reprinted by permission of the authors. This paper originally appeared in Computer Communications, Vol. 13. No. 9. 1990.
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© 1999 Springer-Verlag Berlin Heidelberg
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Weihmayer, R., Brandau, R. (1999). Cooperative Distributed Problem Solving for Communication Network Management. In: Hayzelden, A.L.G., Bigham, J. (eds) Software Agents for Future Communication Systems. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-58418-3_10
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DOI : https://doi.org/10.1007/978-3-642-58418-3_10
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COMMENTS
In computing cooperative distributed problem solving is a network of semi-autonomous processing nodes working together to solve a problem, typically in a multi-agent system.
Cooperative distributed problem solving (CDPS) is a branch of artificial intelligence research that studies how intelligent agents coordinate their activities to collectively solve problems that are beyond their individual capabilities.
abstraction, creating a complex interdependence between 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 nat.
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.
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.
Two forms of cooperation in distributed problem solving are considered: task-sharing and result-sharing. In the former, nodes assist each other by sharing the computational load for the execution of subtasks of the overall problem.
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.
This dissertation describes a framework for cooperative distributed problems solving (CDPS) and how this framework can be used to solve the class of problems comprised of semi-independent sub-problems.
In this article, we illustrate the motivations for distributed problem solving and provide an overview of two distributed problem‐solving models, namely distributed constraint‐satisfaction problems (DCSPs) and distributed constraint‐optimization problems (DCOPs), and some of their algorithms.
Cooperative distributed problem solving is a network of semi-autonomous processing nodes working together to solve a problem, typically in a multi-agent system.