Types and Levels of Knowledge

- Overview

What distinguishes humans from other animals or machines is our "conscience". While scientists often find it difficult to explain what conscience is, one can agree that it is the sum of our memory, that is, all the knowledge we have gathered so far. This knowledge creates different personalities that make humans behave differently and act differently. 

All human abilities, therefore, derive from this aggregated knowledge. Therefore, the prior knowledge that the teacup is hot prevents us from touching it. If we are going to make AI more complex, we need to provide them with more and more complex information about our world to perform complex tasks, which leads to the concept of knowledge representation in AI.

- Kinds of Knowledge Represented in AI Systems

We have some concepts that are completely foreign to machines, such as intuition, intention, prejudice, belief, judgment, common sense, etc., while some knowledge is straightforward, such as knowing certain facts, general knowledge about objects, events, people, academic Subjects, languages, and other immediate things that machines have been able to understand with some success. 

With Knowledge Representation and Reasoning (KR, KRR), we now have to represent this information in a machine-understandable format and make AI systems truly intelligent. Knowledge here would mean providing and storing information about the environment, reasoning would deduce this stored information, and intelligence would mean making decisions and actions based on knowledge and reasoning.

In order to solve the complex problems encountered in AI, one generally needs a large amount of knowledge, and suitable mechanisms for representing and manipulating all that knowledge. Let us first consider what kinds of knowledge might need to be represented in AI systems.

Following are the kinds of knowledge which needs to be represented in AI systems: 

• Objects: All the facts about objects in our world domain. E.g., Guitars contains strings, trumpets are brass instruments.
• Events: Events are the actions which occur in our world. Steve Vai played the guitar in Frank Zappa's band.
• Performance: It describe behavior (like playing the guitar) 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. This can be regarded as the knowledge level.
• Knowledge Base: It is the main component of any human being to have a knowledge base. This refers to a set of information about any discipline, field, etc. For example, a knowledge base about building roads. 

 We can structure these entities at two levels:

• The knowledge level - at which facts are described.
• The symbol level - at which representations of objects are defined in terms of symbols that can be manipulated in programs. 

- Types of knowledge

Knowledge is awareness or familiarity gained by experiences of facts, data, and situations. Given an understanding of the complexity of knowledge representation in AI, it is clear that to represent knowledge to machines, we must first identify and classify different types of knowledge. 

While above we have done so to some extent, here are the formal terms and definitions by which knowledge can be represented. Following are the types of knowledge in artificial intelligence: 

• Declarative Knowledge
• Procedural Knowledge
• Meta-knowledge
• Heuristic knowledge
• Structural knowledge

- Declarative Knowledge

Declarative knowledge is the piece of knowledge that stores factual information in memory, which seems static in nature. These can be things or events or processes, and the domain of such knowledge finds relationships between events or things.

- Procedural Knowledge

Procedural knowledge is less common than declarative knowledge and is also known as imperative knowledge. It has the potential to announce the completion of something. It is commonly used by modern mobile robots, which can plan attacks on buildings or perform navigation in rooms. If we consider implanting declarative knowledge into modern robots, they will only be assigned a map rather than detailed plans to attack buildings.

- Meta-knowledg

In the field of AI, the knowledge of predefined knowledge is called meta-knowledge. Studies of planning, labeling, and learning are some examples of meta-knowledge. The model tends to change over time and use different specifications. Knowledge engineers can utilize different forms of meta-knowledge given below: Accuracy, suitability, evaluation, consistency, completeness, disambiguation, reason, age, purpose, source, reliability.

- Heuristic knowledge

Heuristic knowledge is also known as shallow knowledge, and it follows the principle of rules of thumb. It is very effective in reasoning because it solves problems based on records of past problems or problems compiled by experts. It provides knowledge based on experience gleaned from past problems.

- Structural knowledge

Structural knowledge is the most basic knowledge to use and apply when solving problems. It tries to find out the relationship between concepts and objects.

[More to come ...]