2026-09-19T19:26:56Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/296732022-01-13T07:54:29Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Howard Shrobe.
Kochman, Robert W. (Robert Walter), 1979-
Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2006-03-24T16:13:59Z
2006-03-24T16:13:59Z
2003
2003
http://hdl.handle.net/1721.1/29673
53833676
Thesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2003.
Includes bibliographical references (p. 51-52).
Intelligent environments are becoming more complex, involving greater numbers of more sophisticated devices and agents. As complexity increases, it becomes difficult to build agents that effectively use the resources in their space. Agents may not know which resources are present in a given space, and they are almost certainly do not know which resources are inoperative or being used by other agents. To address this problem, this paper introduces PrefMan, a new resource management system for intelligent environments. To use this system, agents simply request a particular service type and give preferences over resource attributes. T he system keeps track of resources, their types, and their availability, and uses the preferences to intelligently allocate resources to the requesting agent. This paper describes PrefMan in detail and illustrates why it is an effective solution to the resource management problem.
by Robert W. Kochman, Jr.
M.Eng.
52 p.
1477654 bytes
1477461 bytes
application/pdf
application/pdf
eng
Massachusetts Institute of Technology
M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
http://dspace.mit.edu/handle/1721.1/7582
Electrical Engineering and Computer Science.
Decision theoretic resource management for intelligent environments
Thesis
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<Abstract>Intelligent environments are becoming more complex, involving greater numbers of more sophisticated devices and agents. As complexity increases, it becomes difficult to build agents that effectively use the resources in their space. Agents may not know which resources are present in a given space, and they are almost certainly do not know which resources are inoperative or being used by other agents. To address this problem, this paper introduces PrefMan, a new resource management system for intelligent environments. To use this system, agents simply request a particular service type and give preferences over resource attributes. T he system keeps track of resources, their types, and their availability, and uses the preferences to intelligently allocate resources to the requesting agent. This paper describes PrefMan in detail and illustrates why it is an effective solution to the resource management problem.</Abstract>
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