Knowledge Representation Issues

Knowledge Representation Issues

• Various ways to represent knowledge, including predicate calculus, procedural, network, and structured representations.
• Each type of representation has its own set of problems, including hierarchies and inheritance, and exceptions.

Evaluating a Knowledge Representation

• Naturalness, uniformity, and understandability are important considerations.
• Degree to which knowledge is explicit (declarative) or embedded in procedural code is crucial.
• Modularity and flexibility of the knowledge base are also important.
• Efficiency of knowledge retrieval and the heuristic power of the inference procedure are key considerations.

Multiple Knowledge Representations

• No single knowledge representation method is ideally suited for all tasks.
• Multiple knowledge representations can be used, each tailored to a different subtask.
• Production rules and frames work well in practice.
• Object-oriented knowledge representations, such as hypermedia, can also be used.

Knowledge Representation Requirements

• Knowledge representation must support acquiring knowledge, retrieving knowledge, and reasoning.
• Once acquired, knowledge must be organized for use.

Knowledge Base and Inference Mechanism

• A knowledge base forms the system's intelligence source.
• An inference mechanism uses the knowledge base to reason and draw conclusions.
• The knowledge base and inference mechanism are used to answer questions, solve problems, or make decisions within the domain.

Logical Representations

• Symbolic logic is a system of rules and procedures that permits the drawing of inferences from various premises.
• Basic forms of computational logic include propositional logic and predicate logic.
• Propositional logic deals with statements that are either true or false.
• Predicate logic breaks a statement down into component parts, including objects, object characteristics, or object assertions.

Other Representation Schemes

• Lists are used to represent hierarchical knowledge.
• Decision tables are used to organize knowledge in a spreadsheet format.
• Decision trees are used to simplify the knowledge acquisition process.
• O-A-V triplets are used to represent objects, attributes, and values.

Representative O-A-V Items

• Objects may be physical or conceptual.
• Attributes are the characteristics of the objects.
• Values are specific measures of the attributes.
• Examples of O-A-V triplets include house-bedroom-number, house-color-value, and admission to a university-GPA-value.