Costless Expert Systems Development and Re-engineering

Symbolic AI is indispensable for the current LLM agents that are used for example to reason the context of the questions. An expert system is a symbolic AI that can explain the reasoning it reached to, which typically is a rule-based system has been attractive for different domains such as medicine, agriculture, and operations. On average, these systems involve hundreds of rules that are instable; moreover, they are coded at low levels of abstraction. Therefore, designing and reengineering an expert system is still costly and needs technical knowledge because of the manual process and maintaining of a low-level abstraction. On the other hand, model-driven architecture (MDA) has proven to be a successful technology that raised the abstraction level and formalized it to automate software development. It specifies business aspects in the platform-independent model (PIM) and implementation aspects in a platform-specific model (PSM). It then automates mapping between them using a standard mapping language called Query- View- Transform QVT. This paper argues that utilizing MDA principles such as the automation and abstractions represented by the descriptor PIM and PSM and mappings metamodels will not only overcome the instability of rules of expert systems, but also provides new insights for its usage. Therefore, this work proposes an MDA-compliant methodology that adopts a UML sequence diagram, a class diagram for the PIM descriptor, and a generic PSM) based on production rules. Moreover, a UML profile to support lacking features in the sequence model has been developed. However, the paper argues for a new kind of process-oriented expert system. Therefore, it not only allows domain experts to develop or participate in expert systems but also reduces the cost of developing new systems and re-engineering or maintenance of the critical and large-scale legacy expert systems.

@article{Alsharidi2024,
  title     = {Costless Expert Systems Development and Re-engineering},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {15},
  number    = {1},
  year      = {2024},
  publisher = {The Science and Information Organization},
  author    = {Manal Alsharidi and Abdelgaffar Hamed Ali},
  doi       = {10.14569/IJACSA.2024.0150130},
  url       = {https://doi.org/10.14569/IJACSA.2024.0150130}
}