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dc.contributor.authorKunde, Dietmar
dc.contributor.authorDarken, Christian J.
dc.contributor.otherMOVES Institute
dc.date2005
dc.date.accessioned2013-09-25T22:57:58Z
dc.date.available2013-09-25T22:57:58Z
dc.date.issued2005
dc.identifier.citationProceedings of BRIMS 2005.
dc.identifier.urihttp://hdl.handle.net/10945/36607
dc.description.abstractNearly all armies of the Western Hemisphere use modeling and simulation tools as an essential part for analysis and training their leaders and war fighters. Tremendous resources have been applied to increase the level of fidelity and detail with which real combat units are represented in computer simulations. Current models digress from Lanchester equations used for modeling the big Cold War scenarios towards modeling of individual soldier capabilities and behavior in the post Cold War environment and increasingly important asymmetric warfare scenarios. Although improvements in computer technology support more and more detailed representations, human decision making is still far away from being automated in a realistc way. Many "decisions" within a simulation are based on rules and/or stochastic processes (qualified coin tossing) and hardly at all on cognitive processes. One cognitive model in naturialistic decision making is the Recognition Primed Decision Model developed by Klein and Associates. It decribes how the actual process humans use to come up with decisions in certain situations is radically different from the traditional model of rational decision modeling. Mental Simulation is an essential part of this model in order to picture possible outcomes in the future for given courses of actions. This paper describes the current development of a computatinal model for mental simulation and the initial results of experiments conducted with a prototype in a combat simulation envirnment.en_US
dc.description.abstractNearly all armies of the Western Hemisphere use modeling and simulation tools as an essential part for analysis and training their leaders and war fighters. Tremendous resources have been applied to increase the level of fidelity and detail with which real combat units are represented in computer simulations. Current models digress from Lanchester equations used for modeling the big Cold War scenarios towards modeling of individual soldier capabilities and behavior in the post Cold War environment and increasingly important asymmetric warfare scenarios. Although improvements in computer technology support more and more detailed representations, human decision making is still far away from being automated in a realistic way. Many â decisionsâ within a simulation are based on rules and/or stochastic processes (qualified coin tossing) and hardly at all on cognitive processes. One cognitive model in naturalistic decision making is the Recognition Primed Decision Model developed by Klein and Associates. It describes how the actual process humans use to come up with decisions in certain situations is radically different from the traditional model of rational decision making. Mental Simulation is an essential part of this model in order to picture possible outcomes in the future for given courses of actions. This paper describes the current development of a computational model for mental simulation and the initial results of experiments conducted with a prototype in a combat simulation environment.en_US
dc.rightsThis publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. As such, it is in the public domain, and under the provisions of Title 17, United States Code, Section 105, may not be copyrighted.en_US
dc.titleEvent Prediction for Modeling Mental Simulation in Naturalistic Decision Makingen_US
dc.contributor.corporateNaval Postgraduate School, Monterey, California
dc.contributor.departmentComputer Science (CS)
dc.subject.authormental simulationen_US
dc.subject.authornaturalistic decision makingen_US
dc.subject.authorevent predictionen_US
dc.subject.authorcombat simulationen_US
dc.subject.authorCombat XXIen_US


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