Humans are best at understanding, reasoning, and interpreting knowledge. Human knows things, which is knowledge and as per their knowledge they perform various actions in the real world. But how machines do all these things comes under knowledge representation and reasoning. We have to induce right Knowledge, Intelligence and reasoning in the Machine to make it intelligent so that it can process to take right decision.
There are 3 factors which are put into the machine to makes it valuable:
Knowledge : The information related to the environment is stored in the machine.
Reasoning : The ability of the machine to understand the stored knowledge .
Intelligence : The ability of the machine to make decisions on the basis of the stored Information .
If knowledge representation is correct than Machine understanding will be correct. If knowledge representation is wrong then Machine understanding will be wrong.
There are 4 Techniques of representing Knowledge:
- Logical Representation
- Semantic Network Representation
- Frame Representation
- Production Rules
- Logical Representation : Logical Representation is a language with some concrete rules and has no ambiguity in representation. Logical Representation means drawing a conclusion based on various conditions. It is further divided into 2 parts:
a. Propositional logic
b. Predicate logic
Advantages of logical representation:
- Logical representation enables us to do logical reasoning.
- Logical representation is the basis for the programming languages.
Disadvantages of logical Representation:
- Logical representation technique may not be very natural, and inference may not be so efficient.
- Logical representations have some restrictions and are challenging to work with.
- Logical representation is the basis for the programming languages.
2. Semantic Network Representation : Semantic means “meaning” and Network means “graph”. ie, semantic networks means “meaningful graph”. In Semantic Network representation Knowledge is stored into the system in the form of a graph. Eg: Google Graph.
Nodes : Objects
Arrow: Relationship between the objects
Such techniques show the connectivity of one object with another object.
Advantages of Semantic network:
- Semantic networks are a natural representation of knowledge.
- They convey meaning in a transparent manner.
- These networks are simple and easily understandable.
Disadvantages of Semantic network:
- Semantic networks take more computational time at runtime as we need to traverse the complete network tree to answer some questions. It might be possible in the worst case scenario that after traversing the entire tree, we find that the solution does not exist in this network.
- These types of representations are inadequate as they do not have any equivalent quantifier, e.g., for all, for some, none, etc.
- These networks are not intelligent and depend on the creator of the system.
3. Frame Representation : It is a record like structure which consists of a collection of attributes & its values to describe an entity in the world. Eg: in the form of Table.
Advantages of frame representation:
- The frame knowledge representation makes the programming easier by grouping the related data.
- The frame representation is comparably flexible and used by many applications in AI.
- It is very easy to add slots for new attribute and relations.
- It is easy to include default data and to search for missing values.
- Frame representation is easy to understand and visualise.
Disadvantages of frame representation:
- In frame system inference mechanism is not be easily processed.
- Inference mechanism cannot be smoothly proceeded by frame representation.
- Frame representation has a much generalised approach.
4. Rules : knowledge is in the form of “If and Then” statement .
Advantages of Production rule:
- The production rules are expressed in natural language.
- The production rules are highly modular, so we can easily remove, add or modify an individual rule.
Disadvantages of Production rule:
- Production rule system does not exhibit any learning capabilities, as it does not store the result of the problem for the future uses.
- During the execution of the program, many rules may be active hence rule-based production systems are inefficient.
There is one more Technique of representing knowledge. Which is “Script Representation”.
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