BRECCIA: A novel multi-source fusion framework for dynamic geospatial data analysis. Geospatial Intelligence analysis involves the combination of multi-source information expressed in logical form (as sentences or statements), computational form (as numerical models of physics or other processes), and sensor data (as measurements from transducers). Each of these forms has its own way to describe uncertainty or error: e.g., frequency models, algorithmic truncation, floating point roundoff, Gaussian distributions, etc. We propose BRECCIA, a Geospatial Intelligence analysis system, which receives information from humans (as logical sentences), simulations (e.g., weather or environmental predictions), and sensors (e.g. cameras, weather stations, microphones, etc.), where each piece of information has an associated uncertainty; BRECCIA then provides responses to user queries based on a new probabilistic logic system which determines a coherent overall response to the query and the probability of that response; this new method avoids the exponential complexity of previous approaches. In addition, BRECCIA attempts to identify concrete mechanisms (proposed actions) to acquire new data dynamically in order to reduce the uncertainty of the query response. The basis for this is a novel approach to probabilistic argumentation analysis
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- Henderson, T. C.; Simmons, R.; Serbinowski, B.; Cline, M.; Sacharny, D.; Fan, X.; Mitiche, A.: Probabilistic sentence satisfiability: an approach to PSAT (2020)