Dimensionality analysis of a simulation outcome space
Investigates the dimensionality characteristics of the outcome space of a combat simulation. The independent state variables of all of the outcome states for a simulation run for given event management policies were analyzed using techniques based on principal component analysis and singular value d...
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creator | Gilmer, J.B. Sullivan, F.J. |
description | Investigates the dimensionality characteristics of the outcome space of a combat simulation. The independent state variables of all of the outcome states for a simulation run for given event management policies were analyzed using techniques based on principal component analysis and singular value decomposition, to give metrics for dimensionality. The number of dimensions in the outcome space is indicative of variety of possible outcomes, a potentially important property in hierarchical simulation. Events were managed using random choices, multi-trajectory methods designed to give greater preference to high-probability trajectories, and by various methods guided by analysis of the impact of the various events. The number of dimensions could not be increased greatly by the event management techniques used for selecting event outcomes for multi-trajectory resolution. Beyond 1000 replication runs, the size of the state space did not even strongly influence the metrics. |
doi_str_mv | 10.1109/WSC.2001.977352 |
format | Conference Proceeding |
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The independent state variables of all of the outcome states for a simulation run for given event management policies were analyzed using techniques based on principal component analysis and singular value decomposition, to give metrics for dimensionality. The number of dimensions in the outcome space is indicative of variety of possible outcomes, a potentially important property in hierarchical simulation. Events were managed using random choices, multi-trajectory methods designed to give greater preference to high-probability trajectories, and by various methods guided by analysis of the impact of the various events. The number of dimensions could not be increased greatly by the event management techniques used for selecting event outcomes for multi-trajectory resolution. 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The independent state variables of all of the outcome states for a simulation run for given event management policies were analyzed using techniques based on principal component analysis and singular value decomposition, to give metrics for dimensionality. The number of dimensions in the outcome space is indicative of variety of possible outcomes, a potentially important property in hierarchical simulation. Events were managed using random choices, multi-trajectory methods designed to give greater preference to high-probability trajectories, and by various methods guided by analysis of the impact of the various events. The number of dimensions could not be increased greatly by the event management techniques used for selecting event outcomes for multi-trajectory resolution. Beyond 1000 replication runs, the size of the state space did not even strongly influence the metrics.</description><subject>Analytical models</subject><subject>Calibration</subject><subject>Context modeling</subject><subject>Design methodology</subject><subject>Discrete event simulation</subject><subject>Extraterrestrial measurements</subject><subject>Libraries</subject><subject>Principal component analysis</subject><subject>Singular value decomposition</subject><subject>State-space methods</subject><isbn>0780373073</isbn><isbn>9780780373075</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2001</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNotj81qwzAQhAWl0DbNudCTXsDuyitp5WNxfyHQQ1J6DJIsgYodh8g5-O0rSOfywQwMM4w9CKiFgPbpZ9vVDYCoWyJUzRW7AzKAhEB4w9Y5_0KRAir2LVMvaQyHnKaDHdK8cFu45JT5FLnlOY3nwc4l5dN59tMYeD5aH-7ZdbRDDut_rtj32-uu-6g2X--f3fOmSgLkXHmNoW-lQCO1wQgUlYg-OOcbB8KRMEZLpWRv0KPTRptitmUd9U1wBLhij5feFELYH09ptKdlfzmGf8CqQow</recordid><startdate>2001</startdate><enddate>2001</enddate><creator>Gilmer, J.B.</creator><creator>Sullivan, F.J.</creator><general>IEEE</general><scope>6IE</scope><scope>6IH</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIO</scope></search><sort><creationdate>2001</creationdate><title>Dimensionality analysis of a simulation outcome space</title><author>Gilmer, J.B. ; Sullivan, F.J.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i104t-c63ed941384683f07f51fcebbc2b01b718864554d83c3b68681b790007d2eb703</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2001</creationdate><topic>Analytical models</topic><topic>Calibration</topic><topic>Context modeling</topic><topic>Design methodology</topic><topic>Discrete event simulation</topic><topic>Extraterrestrial measurements</topic><topic>Libraries</topic><topic>Principal component analysis</topic><topic>Singular value decomposition</topic><topic>State-space methods</topic><toplevel>online_resources</toplevel><creatorcontrib>Gilmer, J.B.</creatorcontrib><creatorcontrib>Sullivan, F.J.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan (POP) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP) 1998-present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Gilmer, J.B.</au><au>Sullivan, F.J.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Dimensionality analysis of a simulation outcome space</atitle><btitle>Proceeding of the 2001 Winter Simulation Conference (Cat. No.01CH37304)</btitle><stitle>WSC</stitle><date>2001</date><risdate>2001</risdate><volume>1</volume><spage>663</spage><epage>671 vol.1</epage><pages>663-671 vol.1</pages><isbn>0780373073</isbn><isbn>9780780373075</isbn><abstract>Investigates the dimensionality characteristics of the outcome space of a combat simulation. The independent state variables of all of the outcome states for a simulation run for given event management policies were analyzed using techniques based on principal component analysis and singular value decomposition, to give metrics for dimensionality. The number of dimensions in the outcome space is indicative of variety of possible outcomes, a potentially important property in hierarchical simulation. Events were managed using random choices, multi-trajectory methods designed to give greater preference to high-probability trajectories, and by various methods guided by analysis of the impact of the various events. The number of dimensions could not be increased greatly by the event management techniques used for selecting event outcomes for multi-trajectory resolution. Beyond 1000 replication runs, the size of the state space did not even strongly influence the metrics.</abstract><pub>IEEE</pub><doi>10.1109/WSC.2001.977352</doi></addata></record> |
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source | IEEE Electronic Library (IEL) Conference Proceedings |
subjects | Analytical models Calibration Context modeling Design methodology Discrete event simulation Extraterrestrial measurements Libraries Principal component analysis Singular value decomposition State-space methods |
title | Dimensionality analysis of a simulation outcome space |
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