About: Cooperative distributed problem solving is a research topic. Over the lifetime, 72 publications have been published within this topic receiving 9765 citations.
TL;DR: In this article, the contract net protocol has been developed to specify problem-solving communication and control for nodes in a distributed problem solver, where task distribution is affected by a negotiation process, a discussion carried on between nodes with tasks to be executed and nodes that may be able to execute those tasks.
Abstract: The contract net protocol has been developed to specify problem-solving communication and control for nodes in a distributed problem solver. Task distribution is affected by a negotiation process, a discussion carried on between nodes with tasks to be executed and nodes that may be able to execute those tasks.
TL;DR: A framework called the contract net is presented that specifies communication and control in a distributed problem solver, and comparisons with planner, conniver, hearsay-ii, and pup 6 are used to demonstrate that negotiation is a natural extension to the transfer of control mechanisms used in earlier problem-solving systems.
TL;DR: The Distributed Vehicle Monitoring Testbed serves as an example of how a testbed can be engineered to permit the empirical exploration of design issues in knowledge AI systems.
Abstract: : 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 problem 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-based AI systems. The testbed is capable of simulating different degrees of sophistication in problem solving knowledge and different 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 configurations and communication channel characteristics can also be independently varied in the simulated network. (Author)