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Contexts and Data Dependencies: A Synthesis
March 1983 (vol. 5 no. 3)
pp. 237-246
Drew Mcdermott, Department of Computer Science, Yale University, New Haven, CT 06520.
Two data-organization devices that have come out of AI re-search are data pools (``contexts'') and data dependencies. The latter are more flexible than the former, and have supplanted them. Data pools offer certain advantages of efficiency, however, so it is worth trying to make the two mechanisms compatible. Doing this requires generalizing the mark-and-sweep algorithms that maintain consistency in a data-dependency network, so that the labels passed around do not simply say whether a datum is IN or OUT, but say which data pools it is present in. The revised algorithm is essentially an algorithm for solving simultaneous Boolean equations. Other mechanisms are needed for per-forming useful chores like maintaining well-founded support links and orchestrating demon calls.
Citation:
Drew Mcdermott, "Contexts and Data Dependencies: A Synthesis," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 5, no. 3, pp. 237-246, March 1983, doi:10.1109/TPAMI.1983.4767388
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