Enhance AI knowledge representation for better problem-solving, decision-making, and reasoning. Optimize data structuring and retrieval techniques for efficiency

1. KNOWLEDGE
REPRESENTATION IN AI

2. Knowledge representation in AI refers to
the process of structuring and
organizing information in a way that
allows artificial intelligence systems to
understand and manipulate that
information. It is a fundamental aspect
of AI because without an effective way
to represent knowledge, machines
would struggle to reason, learn, and
make informed decisions.

3. Different Types of Knowledge Represented in AI
Declarative Knowledge
Structural Knowledge
Procedural Knowledge
Meta Knowledge
Heuristic Knowledge

4. Declarative Knowledge Structural Knowledge
Refers to the facts, objects, and
concepts that allow us to describe
the world around us. It shares the
description of something
expressed in declarative sentences
which is simpler than procedural
language.
Constitutes the problem-solving
knowledge that describes the
relationship between various
concepts or objects and their
descriptions.

5. Procedural Knowledge Meta Knowledge
Also known as imperative knowledge,
procedural knowledge is used to
complete any task with specific rules,
strategies, processes, or agendas. It’s
the type of knowledge which is
responsible for knowing how to do a
particular task and hence relies on the
task we are trying to finish.
As mentioned above, meta
knowledge refers to predefined
knowledge about things that we
are already aware of. This
knowledge typically includes the
study of tagging, planning,
learning, etc.

6. Heuristic Knowledge
Also known as shallow knowledge,
heuristic knowledge is highly used in
the process of reasoning as it can
solve issues based on the
experiences of past problems. Thus,
it provides a knowledge-based
approach to define a problem and
take action.

7. Four Fundamental Knowledge Representation
Techniques in AI
KR
Techniques
Logical
Representation
Semantic
Network
Frame
Representation
Production
Rules

8. In conclusion, knowledge representation in AI is a
foundational and crucial aspect of artificial
intelligence. It involves encoding information about
the world in a format that AI systems can understand,
manipulate, and reason with. Various approaches and
techniques have been developed over the years,
including symbolic representation, semantic networks,
frames, ontologies, and more recently, neural networks
and deep learning methods. The choice of knowledge
representation method depends on the specific
problem and the nature of the domain being modeled.

9. THANK YOU