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2. Explainable artificial intelligence - Wikipedia

   en.wikipedia.org/wiki/Explainable_artificial...

   Explainable AI ( XAI ), often overlapping with interpretable AI, or explainable machine learning ( XML ), either refers to an artificial intelligence (AI) system over which it is possible for humans to retain intellectual oversight, or refers to the methods to achieve this. [1] [2] The main focus is usually on the reasoning behind the decisions ...

3. Rule-based machine learning - Wikipedia

   en.wikipedia.org/wiki/Rule-based_machine_learning

   v. t. e. Rule-based machine learning (RBML) is a term in computer science intended to encompass any machine learning method that identifies, learns, or evolves 'rules' to store, manipulate or apply. [1] [2] [3] The defining characteristic of a rule-based machine learner is the identification and utilization of a set of relational rules that ...

4. Rule-based system - Wikipedia

   en.wikipedia.org/wiki/Rule-based_system

   Rule-based system. In computer science, a rule-based system is a computer system in which domain-specific knowledge is represented in the form of rules and general-purpose reasoning is used to solve problems in the domain. Two different kinds of rule-based systems emerged within the field of artificial intelligence in the 1970s:

5. Expert system - Wikipedia

   en.wikipedia.org/wiki/Expert_system

   A Symbolics 3640 Lisp machine: an early (1984) platform for expert systems. In artificial intelligence (AI), an expert system is a computer system emulating the decision-making ability of a human expert. [1] Expert systems are designed to solve complex problems by reasoning through bodies of knowledge, represented mainly as if–then rules ...

6. Inference engine - Wikipedia

   en.wikipedia.org/wiki/Inference_engine

   Inference engine. In the field of artificial intelligence, an inference engine is a software component of an intelligent system that applies logical rules to the knowledge base to deduce new information. The first inference engines were components of expert systems. The typical expert system consisted of a knowledge base and an inference engine.

7. Commonsense knowledge (artificial intelligence) - Wikipedia

   en.wikipedia.org/wiki/Commonsense_knowledge...

   Using widely held beliefs about everyday objects, or common sense knowledge, AI systems make common sense assumptions or default assumptions about the unknown similar to the way people do. In an AI system or in English, this is expressed as "Normally P holds", "Usually P" or "Typically P so Assume P". For example, if we know the fact "Tweety is ...