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Solution method for cognitive description program based on generation-verification

A cognitive description and program technology, applied in the direction of reasoning methods, etc., can solve problems such as complexity and low efficiency of solution methods, and achieve the effects of improving efficiency, simplifying cognitive description programs, and improving semantics

Active Publication Date: 2013-04-03
SOUTHEAST UNIV
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, so far, no inference engine for this program has appeared. The design and implementation of an inference engine for a cognitive description program can enable the language to be used in practice. The solution of a cognitive description program is a complexity problem, but this solution method is inefficient and complex

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  • Solution method for cognitive description program based on generation-verification
  • Solution method for cognitive description program based on generation-verification
  • Solution method for cognitive description program based on generation-verification

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Embodiment Construction

[0065] Below in conjunction with specific embodiment, further illustrate the present invention, should be understood that these embodiments are only used to illustrate the present invention and are not intended to limit the scope of the present invention, after having read the present invention, those skilled in the art will understand various equivalent forms of the present invention All modifications fall within the scope defined by the appended claims of the present application.

[0066] The technical solution of the present invention will be introduced below from two aspects of system structure and method flow.

[0067] 1) Architecture: figure 1 A realization architecture of cognitive description program reasoning machine is given. The specific description of several main parts is given below.

[0068] parser

[0069] The grammatical analyzer checks the correctness of the syntax of the input cognitive description program and whether the cognitive description program is ...

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Abstract

The invention discloses a solution method for a cognitive description program based on generation-verification. When one cognitive description program is input: firstly, a predicate dependency graph of the cognitive description program is firstly constructed based on morphology and grammar correctness analysis and safety check, block-shaped topological sorting of program blocks is generated, then a forward reasoning technology is used to sequentially generate instantiation program blocks according to the topological sorting, and finally the instantiation cognitive description program is generated; secondly, a constant-true constant-false character set of the instantiation cognitive description program is obtained and used for deleting redundancy rules and redundancy characters so as to simplify the program; then, dependency relationship of subjective characters is confirmed according to the predicate dependency graph, and possible solution of the program is generated in a heuristic mode according to the dependency relationship of subjective characters; and after that, subjective character values are verified to be correct or not, and whether the possible solution is of the cognitive description program or not is confirmed. The whole solution method adopts a backtracking process to generate all of possible solutions and verify obtained all of solutions.

Description

technical field [0001] The invention relates to a method for solving a cognitive description program based on generation-verification. The method is based on non-monotone logic reasoning theory, adopts program predicate dependency graph and heuristic search technology, including instantiation, program simplification, generation of possible solutions, and The test determines the final solution in four steps. In the fields of logic programming, knowledge representation, and reasoning. Background technique [0002] The answer set program (answer set program) has strong non-monotonic reasoning ability and is close to natural language, so it has become an important tool for knowledge representation and reasoning in the fields of planning, diagnosis, knowledge management, knowledge-based question answering, constraint solving, etc. . With the emergence of efficient answer set program reasoning machines such as Smodels, DLV, and Clasp, the application prospects of answer set prog...

Claims

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Application Information

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IPC IPC(8): G06N5/04
Inventor 崔荣存张志政
Owner SOUTHEAST UNIV
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