Held at the ACM SIGAda Summer Working Group meeting and Washington Ada Symposium
June 27 1995
Artificial Intelligence technology is proving to be of value in solving complex problems requiring reasoning on dynamic, uncertain, and incompletely specified domains. AI has been successfully applied in a range of applications including, for example, decision support systems and situation assessment - for example, target classification and early warning systems - by allowing the manipulation of vast amounts of information generated by modern sensors and intelligence systems.
Although these next generation embedded systems possess some unique special purpose requirements, they must be integrated with existing conventional software per forming conventional real-time tasks. The integration of matured AI methods and techniques with conventional software engineering remains difficult and poses both implementation and conceptual problems.
Our ultimate goal is to understand what problems the embedded AI community (specially the defense establishment) face and what solutions are potentially or actually available to address these problems. As a result, we would be able to identify potential technology that makes the practice of software engineering more effective in solving embedded AI implementation problems. This introduces new conceptual and engineering problems into traditional AI and important software engineering challenges; these include:
For additional information and address to send submissions:Dr. Jorge L. Díaz-Herrera