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  2. Ripple-down rules - Wikipedia

    en.wikipedia.org/wiki/Ripple-down_rules

    Ripple-down rules consist of a data structure and knowledge acquisition scenarios. Human experts' knowledge is stored in the data structure. The knowledge is coded as a set of rules. The process of transferring human experts' knowledge to Knowledge-based systems in RDR is explained in knowledge acquisition scenario.

  3. List of programming languages for artificial intelligence

    en.wikipedia.org/wiki/List_of_programming...

    Python is a high-level, general-purpose programming language that is popular in artificial intelligence. [1] It has a simple, flexible and easily readable syntax. [ 2 ] Its popularity results in a vast ecosystem of libraries , including for deep learning , such as PyTorch , TensorFlow , Keras , Google JAX .

  4. Inference engine - Wikipedia

    en.wikipedia.org/wiki/Inference_engine

    A trivial example of how this rule would be used in an inference engine is as follows. In forward chaining, the inference engine would find any facts in the knowledge base that matched Human(x) and for each fact it found would add the new information Mortal(x) to the knowledge base. So if it found an object called Socrates that was human it ...

  5. Knowledge acquisition - Wikipedia

    en.wikipedia.org/wiki/Knowledge_acquisition

    Knowledge acquisition is the process used to define the rules and ontologies required for a knowledge-based system. The phrase was first used in conjunction with expert systems to describe the initial tasks associated with developing an expert system, namely finding and interviewing domain experts and capturing their knowledge via rules ...

  6. Expert system - Wikipedia

    en.wikipedia.org/wiki/Expert_system

    An expert system is an example of a knowledge-based system. Expert systems were the first commercial systems to use a knowledge-based architecture. In general view, an expert system includes the following components: a knowledge base, an inference engine, an explanation facility, a knowledge acquisition facility, and a user interface. [48] [49]

  7. Machine learning - Wikipedia

    en.wikipedia.org/wiki/Machine_learning

    Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn from data and generalize to unseen data, and thus perform tasks without explicit instructions. [1]

  8. Knowledge representation and reasoning - Wikipedia

    en.wikipedia.org/wiki/Knowledge_representation...

    Knowledge representation and reasoning (KRR, KR&R, or KR²) is a field of artificial intelligence (AI) dedicated to representing information about the world in a form that a computer system can use to solve complex tasks, such as diagnosing a medical condition or having a natural-language dialog.

  9. Knowledge-based systems - Wikipedia

    en.wikipedia.org/wiki/Knowledge-based_systems

    Frames, for example, are a way representing world knowledge using techniques that can be seen as analogous to object-oriented programming, specifically classes and subclasses, hierarchies and relations between classes, and behavior [clarification needed] of objects. With the knowledge base more structured, reasoning could now occur not only by ...

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