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16 June 1997 Formal methods of automated reasoning for situational estimation
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Abstract
Most research and prototype development of automated methods for situational estimation in the data fusion community have applied heuristic approaches coupled to techniques for uncertainty management. Reasoning theorists would label these methods as those of the parametric reasoning class. Such methods are reasonable when the so-called 'closed world' assumption can be confidently applied (ability to full pre- specify expected conditions) which might have been reasonable in the 'Soviet Era' but would appear fragile/brittle for current-day application. Motivated in part by these considerations and by the need to consider much more cost- effective knowledge-based-system development in an era of declining budgets, this paper offers some discussion on the applicability of more formal methods of reasoning for KBS. It is concluded that strictly formal methods for real-world applications require yet further theoretical development but that movement toward formalization is possible.
© (1997) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
James Llinas "Formal methods of automated reasoning for situational estimation", Proc. SPIE 3067, Sensor Fusion: Architectures, Algorithms, and Applications, (16 June 1997); https://doi.org/10.1117/12.276120
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