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- W72520811 abstract "An expert system that monitors complex activity requires knowledge that is difficult to capture with standard rule-based representations. The focus of this research has been to design and implement script-based reasoning techniques integrated into a rule-based expert system for situation monitoring to address this problem. The resulting expert system, Scripted ANalyst (SCAN), for battlefield monitoring has the capability of reasoning about tactical situations as they develop and providing plausible explanations of activities as inferred from intelligence reports. Sequences of events are monitored through the use of script templates which are matched against events and the time relations between events. SCAN detects causal relations between events, generates multiple hypotheses, fills in information gaps, and sets up expectations about timedependent events--all features a simple rule-based expert system cannot easily provide. 1. IntrocSuction This paper describes the research and development of artificial intelligence paradigms and structures needed to build an expert system decision aid for army tactical intelligence staff as they hypothesize about a battlefield situation. In monitoring the situation to support force command and control (C2) d ecision-making, a military intelligence analyst must not only interpret the force disposition given reports from multiple sources but must also formulate a sense of how a situation is developing over a long period of time. An expert system designed to monitor sequences of events can help the analyst keep track of the many possible explanations of ongoing actions and intentions and recognize any unusual or unexpected activity. However, such a system must have internal representations to deal with sophisticated time and order relationships so that it can generate multiple hypotheses, fill in information gaps, and set up expectations. It must notice trends and shifts in the action and activity and provide clear explanations of its inferencing. This inferencing includes the ability to expect that certain events have occurred based on information about related events without necessarily asserting these through the rule base. All this must be done in an environment where information is potentially sparse or misleading." @default.
- W72520811 created "2016-06-24" @default.
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- W72520811 date "1987-01-01" @default.
- W72520811 modified "2023-09-26" @default.
- W72520811 title "Scripf-Based easoning For Situatio" @default.
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