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ISSN-L 2065 - 8168
ISSN (e) 2068 - 2077
ISSN (p) 2065 - 8168

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Propositional calculation for expert systems in economics

 

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  1. Authors:
      • Emilia VASILE, email: rector@univath.ro, Afiliation: Athenaeum University, Bucharest, Romania
      • Dănuţ-Octavian SIMION, email: danut_so@yahoo.com, Afiliation: Athenaeum University, Bucharest, Romania
      • George CALOTĂ, email: gcalota2003@yahoo.com, Afiliation: Athenaeum University, Bucharest, Romania

    Pages:
      • 9|19

  2. Keywords: Propositional calculation, expert systems, business environment, programming rules, information systems

  3. Abstract:

    The paper presents the propositional calculation for expert systems in economics that ensure the logic for advanced programming language such as Prolog. An Expert System (ES) is a complex application (a software program) that explores a multitude of given knowledge to get new conclusions about difficult activities to examine using methods similar to human experts. An expert system can succeed in problems without a deterministic algorithmic solution. The inference engine is the one to determine all the rules that are activated, thus making the correlation between the facts base and the rule base, and then it also selects one of the rules that are activated at a given moment, which it puts into execution. Execution of a rule means the implementation of the right part of it, which may have one or more effects such as modifying the base of facts, sending messages to the operator, or transmitting signals to the outside, depending on the actions provided for in part to conclude the rule. The inference engine initiates a search in the knowledge base trying to solve the problem proposed by matching the left parts of the rules with the facts in the working memory and executing the rules that are enabled. ES may ask questions to the user when working when he gets stuck (he does not solve the proposed problem and cannot activate any rule) by using this dialog in the same interface. This also illustrates the difference in principle from conventional programming: the path that the inference engine will follow to reach the solution is not predetermined. It depends on the user’s problem (the baseline state of the facts) and the responses the ES receives during work.

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