Event Prediction for Modeling Mental Simulation in Naturalistic Decision Making
Abstract
Nearly 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. Nearly 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.
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