| deKleer, J., Doyle, J., Rich, C., Steele, G., and Sussman, G. AMORD--A deductive procedure system. Memo 435. MIT Artificial Intelligence Lab., Cambridge, Mass., Jan. 1978. |
....knowledge, but has also beert extensively criticized either for being too general or too inflexible. General deductive procedures for predicate logic easily go out of control. There have been a few attempts to design systems which include facilities for (loosely) controlling the reasoning process [8, 6, 14, 15]. They have provided significant insights in the control patterns used in deductions but very limited performance improvements. Most of the systems based on predicate logic rely on the implicit assumption that the smartness of the system can be concentrated in its deductive capabilities. ....
de Kleer, J., Doyle, J., Rich, C., Steele, G. L. and Sussman, G. J. AMORD: a Deductive Procedure System. AI-Memo 435, MIT, January, 1978.
....to use meta rules capturing domain specific control knowledge for selecting the subgoal to pursue in each inference cycle. Thus, in GRAPES, goal directed control knowledge can reside in procedural conflict resolution mechanisms as well as declarative meta rules. In other RBS schemes, like AMORD [11] and GDD [22] a reasoning component posts goals and then a planning component determines the order of pursuing these goals. AMORD is a general purpose solver that combines truth maintenance and planning facilities. It uses rules that post inference goals to its reasoner and rules that post action ....
deKleer, J., Doyle, J., Steele, G.L., and Sussman, G.J., "AMORD: A Deductive Procedure System," MIT AI Memo No. 435, 1978.
No context found.
deKleer, J., Doyle, J., Rich, C., Steele, G., and Sussman, G. AMORD--A deductive procedure system. Memo 435. MIT Artificial Intelligence Lab., Cambridge, Mass., Jan. 1978.
No context found.
deKleer, J., Doyle, J., Rich, C., Steele, G. L., and Sussman, G. J., AMORD: A Deductive Procedure System. MIT AI Memo No. 435, 1978.
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