Helmut Prendinger, Mitsuru Ishizuka, and Tetsu Yamamoto. The hyper system: Knowledge reformation for efficient first-order hypothetical reasoning. In Pacific Rim International Conference on Artificial Intelligence, pages 93-103, 2000. Home/Search Document Details and Download
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Improving Search in a Hypothetical Reasoning System - Hagen, Sattar, Goodwin (Correct)
....is specified in the database as fact e(0) We conjecture that if this were changed to e.g. fact e(n) where n is the highest numbered vertex, the reverse ordering of literals would result in a similar improve ment. More sophisticated forms of static analysis such as that used in the HYPER system [13] should also be investigated for efficiency boosts when applied to large problems. The representation used for our Hamilton walk problems deliberately avoided variables, so the techniques of the HYPER system were not applicable. It might be possible to apply them to the full adder problem. Using ....
Helmut Prendinger, Mitsuru Ishizuka, and Tetsu Yamamoto. The hyper system: Knowledge reformation for efficient first-order hypothetical reasoning. In Pacific Rim International Conference on Artificial Intelligence, pages 93-103, 2000.
Efficient Consequence Finding - Simon, Val (2001) (4 citations) (Correct)
....the induced hardness overcomes the simplification due to the use of DR instead of Tison, which is clearly counter intuitive. This is not the case for the mult n nor for the bnp 10 50 instances, on which picomp and zres tison failed. Table 5 presents some easier examples, the path kr problems from [Prendinger et al. 2000] (abbreviated p kr) which can be solved by both drcomp and picomp. For comparison with their results, note that we, unlike them, are L 0 V L 1 V Bench. Time #LV LUB Time #P IL V adder 5 0.18 448 0.3 1396 adder 10 0.78 18184 3.6 354172 adder 20 3.51 1.88e 7 36.51 2.09e 10 adder 25 5.88 ....
H. Prendinger, M. Ishizuka, and T. Yamamoto. The Hyper system: Knowledge reformation for efficient first-order hypothetical reasoning. In PRICAI '00, 6th Pacific Rim Int. Conf. on Artificial Intelligence, 2000.
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