Most research into applying AI techniques to real-time control problems has limited the power of AI methods or embedded \reactivity" in an AI system. We present an alternative, cooperative architecture that uses separate AI and real-time subsystems to address the problems for which each is designed; a structured interface allows the subsystems to communicate without compromising their respective performance goals. By reasoning about its own bounded reactivity, CIRCA can guarantee that it will meet hard deadlines while still using unpredictable AI methods. With its abilities to guarantee or trade o the timeliness, precision, con dence, and completeness of its output, CIRCA provides more exible performance than previous systems.
This work was supported by NASA under contract NNL13AC67T. Any opinions, findings, conclusions, or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of NASA or the U.S. Government. Several individuals contributed to the study described in this report. Siddhartha Bhattacharyya of Rockwell Collins provided general oversight, outline of the sections and characterization. Darren Cofer of Rockwell Collins developed sections on certification challenges and also on the general oversight. Dave Musliner, Joseph Mueller and Eric Engstrom provided insight into intelligent and adaptive control algorithms. Kelly J. Hayhurst from NASA Langley Research Center provided valuable input regarding adaptive systems and certification. Many researchers from academia, industry and government agencies provided insight into adaptive systems.The use of trademarks or names of manufacturers in this report is for accurate reporting and does not constitute an official endorsement, either expressed or implied, of such products or manufacturers by the National Aeronautics and Space Administration.
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