Global/Local Dynamic Models

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Many dynamic systems involve a number of entities that are largely independent of each other but interact with each other via a subset of state variables. We present global/local dynamic models (GLDMs) to capture these kinds of systems. In a GLDM, the state of an entity is decomposed into a globally influenced state that depends on other entities, and a locally influenced state that depends only on the entity itself. We present an inference algorithm for GLDMs called global/local particle filtering, that introduces the principle of reasoning globally about global dynamics and locally about local dynamics. We have applied GLDMs ... continued below

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Pfeffer, A; Das, S; Lawless, D & Ng, B October 10, 2006.

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Many dynamic systems involve a number of entities that are largely independent of each other but interact with each other via a subset of state variables. We present global/local dynamic models (GLDMs) to capture these kinds of systems. In a GLDM, the state of an entity is decomposed into a globally influenced state that depends on other entities, and a locally influenced state that depends only on the entity itself. We present an inference algorithm for GLDMs called global/local particle filtering, that introduces the principle of reasoning globally about global dynamics and locally about local dynamics. We have applied GLDMs to an asymmetric urban warfare environment, in which enemy units form teams to attack important targets, and the task is to detect such teams as they form. Experimental results for this application show that global/local particle filtering outperforms ordinary particle filtering and factored particle filtering.

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PDF-file: 8 pages; size: 0.1 Mbytes

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  • Presented at: International Joint Conference on Artificial Intelligence, Hyderabad, India, Jan 06 - Jan 12, 2007

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  • Report No.: UCRL-CONF-225258
  • Grant Number: W-7405-ENG-48
  • Office of Scientific & Technical Information Report Number: 900155
  • Archival Resource Key: ark:/67531/metadc882876

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  • October 10, 2006

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  • Sept. 22, 2016, 2:13 a.m.

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  • Dec. 5, 2016, 6:26 p.m.

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Pfeffer, A; Das, S; Lawless, D & Ng, B. Global/Local Dynamic Models, article, October 10, 2006; Livermore, California. (digital.library.unt.edu/ark:/67531/metadc882876/: accessed September 20, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.