The goal of the project is to combine specialized domain knowledge with common sense knowledge to create a reasoning system that learns as well as a person and can be applied to a variety of complex tasks. Such a system will significantly expand the kinds of tasks that a computer can learn.

Under the contract, which is administered by the Air Force Research Laboratory, Wright-Patterson AFB, Ohio, BBN's first year research will focus on military medical logistics planning, specifically, a simulation that requires evacuating wounded military personnel and civilians from Fallujah, Iraq to hospitals in Germany and Kuwait.

However, successful demonstration of this system will have implications beyond the ability to automate the medical evacuation planning process by providing the groundwork for automated systems capable of learning other tasks of similar complexity. This will enable a capacity to develop more effective military decision/planning support systems at lower costs and that require less training for human users.

"This program attacks one of the biggest problems in AI," said Mark Berman, vice president, BBN Technologies, "The Integrated Learner will combine traditional machine learning techniques with an AI reasoning system capable of understanding behavior it observes only once.

"This ambitious goal is necessary because, for many of the current and future complex military tasks that could benefit from automation, there simply are not many examples in existence. Although there has been some research into this area, this will be the first deployed system with the capacity to apply general knowledge and reasoning to a task."

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