Being 'lost' is an exemplar of imperfect Situation Awareness/Situation Understanding (SA/SU) -- information/knowledge that is uncertain, incomplete, and/or just wrong. Being 'lost' may be a geo-spatial condition - not knowing/being wrong about where to go or how to get there. More broadly, being 'lost' can serve as a metaphor for uncertainty and/or inaccuracy - not knowing/being wrong about how one fits into a larger world view, what one wants to do, or how to do it. This paper discusses using agent based modeling (ABM) to explore imperfect SA/SU, simulating geo-spatially 'lost' intelligent agents trying to navigate in a virtual world. Each agent has a unique "mental map" -- its idiosyncratic view of its geo-spatial environment. Its decisions are based on this idiosyncratic view, but behavior outcomes are based on ground truth. Consequently, the rate and degree to which an agent's expectations diverge from ground truth provide measures of that agent's SA/SU.
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