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