Two forms of cooperation in distributed problem solving are considered: task-sharing and result-sharing, and the basic methodology is presented and systems in which it has been used are described.
Abstract:
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. In the latter, nodes assist each other by sharing partial results which are based on somewhat different perspectives on the overall problem. Different perspectives arise because the nodes use different knowledge sources (KS's) (e.g., syntax versus acoustics in the case of a speech-understanding system) or different data (e.g., data that is sensed at different locations in the case of a distributed sensing system). Particular attention is given to control and to internode communication for the two forms of cooperation. For each, the basic methodology is presented and systems in which it has been used are described. The two forms are then compared and the types of applications for which they are suitable are considered.
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.
TL;DR: This survey characterizes an emerging research area, sometimes called coordination theory, that focuses on the interdisciplinary study of coordination, that uses and extends ideas about coordination from disciplines such as computer science, organization theory, operations research, economics, linguistics, and psychology.
TL;DR: A multi-agent system (MAS) as discussed by the authors is a distributed computing system with autonomous interacting intelligent agents that coordinate their actions so as to achieve its goal(s) jointly or competitively.
TL;DR: Social scientists in a wide range of fields will find this book an essential tool for research, particularly in sociology, economics, anthropology, geography, organizational theory, political science, social policy, cognitive psychology and cognitive science, and it will also appeal to computer scientists interested in distributed artificial intelligence, multi-agent systems and agent technologies.
TL;DR: An overview of the holonic reference architecture for manufacturing systems as developed at PMA-KULeuven, which shows PROSA shows to cover aspects of both hierarchical as well as heterarchical control approaches.
TL;DR: This report reproduces a thesis of the same title submitted to the Department of Electrical Engineering, Massachusetts Institute of Technology, in partial fulfillment of the requirements for the degree of Doctor of Philosophy, September 1972.
TL;DR: By viewing distributed systems as analogous to human organizations, concepts and theories germane to the management science field of organization theory can be applied.
TL;DR: The issues of the system organization of the HSII system are dealt with, which include a convenient modular structure for incorporating new knowledge into the system at any level, and a system structure suitable for execution on a parallel processing system.
TL;DR: A relaxation process is described and is applied to the detection of smooth lines and curves in noisy, real world images, effective even for curves of low contrast, and even when many curves lie close to one another.
TL;DR: An organization is presented for implementing solutions to knowledge-based AI problems using the hypothesize-and-test paradigm as the basis for cooperation among many diverse and independent knowledge sources.
Q1. What have the authors contributed in "Frameworks for cooperation in distributed problem solving" ?
For each, the basic methodology is presented and systems in which it has been used are described.
Q2. What is the purpose of the answer synthesis?
Answer synthesis is performed in the third phase; that is, integration of subproblem results to achieve a solution to the overall problem.
Q3. How do the authors use negotiation to solve the connection problem?
In order to maximize system concurrency, both nodes with tasks to be executed and nodes ready to execute tasks can proceed simultaneously, engaging each other in a process that resembles contract negotiation to solve the connection problem.
Q4. How many bits must be communicated by each node?
Assume that each of the nodes operates at 108 instructions per second; the computation and communication load is shared equally by all nodes, and the problem-solving architecture is such that one bit must be communicated by each node for every ten instructions that it executes.
Q5. What is the common metaphor for a problem solver?
A familiar metaphor for a problem solver operating in a distributed processor is a group of human experts experienced at working together, trying to complete a large task.
Q6. What is the purpose of the contract net protocol?
The connection that is effected with the contract net protocol is an extension to the pattern-directed invocation used in many AI programming languages (see [5] for anin-depth discussion).
Q7. What is the definition of a block world image?
A blocks world image is a line drawing that shows the edges of a collection of simple objects (e.g., cubes, wedges, and pyramids) in a scene.
Q8. What is the key to achieving consistent image labeling?
Thus the key to achieving consistent image labeling is to compare the label set of each vertex with those of its neighbors and discard inconsistent labels.