Representing the key concepts and relations between the decision variables in some formal manner, typically within a framework suggested by an expert systems shell, i.e. encoding of knowledge in a form that can be used for computer-based problem solving. 

  • Knowledge: Awareness or familiarity gained by experiences of facts, data, and situations. 

The kind of knowledge to be represented in AI systems:

  • Object: All the facts about objects in our world domain. E.g. guitars contain strings, trumpets are brass instruments.
  • Events: Events are the actions which occur in our world.
  • Performance: It describes behaviour which involves knowledge about how to do things.
  • Meta-knowledge: It is knowledge about what we know.
  • Facts: Facts are the truths about the real world and what we represent.
  • Knowledge-Base: The central component of the knowledge-based agents. 
Knowledge Representation in Artificial intelligence

Illustration of knowledge types [javaTpoint]

The various types of knowledge:

  • Declarative (Descriptive) Knowledge: concepts, facts, and objects.
  • Procedural (Imperative) Knowledge: rules, strategies, procedures, agendas, etc.
  • Structural knowledge: relationships between concepts and objects.
  • Heuristic knowledge: rule of thumb, based on previous experiences, awareness of approaches, and which are good to work but not guaranteed.
  • Meta-knowledge: knowledge about the other types of knowledge.

Literature:

  1. [javaTpoint] What is Knowledge Representation? https://www.javatpoint.com/knowledge-representation-in-ai.