In knowledge-based computing, what do we call a computer program that encapsulates domain-specific expertise to solve problems at a near-human specialist level?

Introduction / Context:
Before contemporary data-driven machine learning dominated practice, symbolic AI delivered real-world value via systems that modeled human expert reasoning in narrow domains such as medical diagnosis, configuration, and financial advising. These systems remain an essential part of AI history and are still useful where transparent, rule-based reasoning is required.

Given Data / Assumptions:

• The program stores and applies specialized domain knowledge.
• It aims to make decisions or recommendations similar to a human expert.
• It typically includes a knowledge base and an inference engine.

Concept / Approach:

The standard term is ‘‘expert system.’’ Such a system represents knowledge in production rules or other structured forms and uses forward or backward chaining to infer conclusions. An explanation facility may justify outputs by tracing rule firings, making the system's reasoning auditable and trustworthy in regulated settings.

Step-by-Step Solution:

Verification / Alternative check:

Classic systems like MYCIN (medicine) and XCON (configuration) are universally labeled expert systems, confirming the terminology.

Why Other Options Are Wrong:

Intelligent planner: Focuses on plan generation, not general domain expertise.

Automatic processor / operational symbolizer: Not standard AI nomenclature.

None of the above: Incorrect because a well-accepted term exists.

Common Pitfalls:

Equating any AI with an expert system; modern ML systems differ in representation and learning methods.

Final Answer:

expert system