Yajat Malhotra
  • Resources
  • 🤖Artificial Intelligence
    • Introduction to AI
    • Artificial Agents
    • Knowledge Inferring Systems
    • Problem Solving
  • 🛠️Machine Learning
    • Get Started with Machine Leaning
      • Supervised Learning
      • Unsupervised Learning
Powered by GitBook
On this page
  • Types of Knowledge
  • Cycle of Knowledge Representation
  • Techniques of Knowledge Representation
  • Representation Requirements
  • Approaches to Knowledge Representation

Was this helpful?

  1. Artificial Intelligence

Knowledge Inferring Systems

PreviousArtificial AgentsNextProblem Solving

Last updated 3 years ago

Was this helpful?

Once the knowledge has been imparted to an agent, we need to see what that agent can infer out of that knowledge and manipulation it does.

Types of Knowledge

  1. Declarative - concepts, facts & objects

  2. Structural - problem-solving (concepts - related objects)

  3. Procedural - rules, strategies, procedures, etc.

  4. Meta - knowledge about other types of knowledge

  5. Heuristic - unknown expert knowledge

Cycle of Knowledge Representation

Techniques of Knowledge Representation

  1. Logical Representation

  2. Semantic Network Representation

  3. Frame Representation

  4. Production Rules

Representation Requirements

  • Representation Accuracy - task all relevant knowledge

  • Inferential Adequacy - manipulate new knowledge

  • Inferential Efficiency - productive good/ useful

  • Acquisitional Efficiency - understands the data at all points

Approaches to Knowledge Representation

  1. Simple Relational - in the form of a relational table

  2. Hierarchial/Inheritable

  3. Inferential

🤖
LogoWhat is Knowledge Representation in AI? | Different Techniques | EdurekaEdureka
Semantic Network