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Please use this identifier to cite or link to this item: http://hdl.handle.net/1860/3387

Title: Automatic construction, maintenance, and optimization of dynamic agent organizations
Authors: Sultanik, Evan Andrew
Keywords: Computer Science;Algorithms;Artificial intelligence
Issue Date: 20-Oct-2010
Abstract: The goal of this dissertation is to generate organizational structures that increase the overall performance of a multiagent coalition, subject to the system's complex coordination requirements and maintenance of a certain operating point. To this end, a generalized framework capable of producing distributed approximation algorithms based on the new concept of multidirectional graph search is proposed and applied to a family of connectivity problems. It is shown that a wide variety of seemingly unrelated multiagent organization problems live within this family. Su cient conditions are identi ed in which the approach is guaranteed to discover a solution that is within a constant factor of the cost of the optimal solution. The procedure is guaranteed to require no more than linear|and in some well de ned cases logarithmic|communication rounds. A number of examples are given as to how the framework can be applied to create, maintain, and optimize multiagent organizations in the context of real world problems. Finally, algorithmic extensions are introduced that allow for the framework to handle problems in which the agent topology and/or coordination constraints are dynamic, without signi cant consequences to the general runtime, memory, and quality guarantees.
URI: http://hdl.handle.net/1860/3387
Appears in Collections:Drexel Theses and Dissertations

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