Product Systems in Artificial Intelligence
In the present day, as machines play an important role in businesses, companies are finding new ways to optimize performance. Machines are driving business growth and accelerating automation transformation by adding value to material, energy, and information. Machines aren’t just becoming ubiquitous; they are also getting smarter and more intelligent with each passing day. The self-learning algorithms have helped them learn utilizing the pre-existing data.
Traditionally, machines were dependent on humans to perform to enhance their performance. However, artificial intelligence (AI), machine learning (ML), deep learning (DL) etc., has made machines rely on smarter algorithms and data collected from different sources.
Together, these changes are bringing in an automation revolution spearheaded by artificial intelligence and machine learning. At the forefront of the revolution will be the problem-solving skills of the machines that will help businesses tackle complex situations effectively. In this article, we will explore AI production systems that have the human brain’s cognitive capabilities.
What is a Production System in Artificial Intelligence?
Experts define a production system as a cognitive architecture that represents different rules. These rules and factors are encoded into the system as knowledge, which becomes the mechanism to resolve conflicts and problems.
Generally, machines running primarily on artificial intelligence have rules and regulations embedded into their database. It helps make the right decision and generalize a behavioural pattern, which becomes the paradigm for evaluating different situations. The production system in artificial intelligence uses pre-set behaviour to observe a condition and suggest an action.
Therefore, rule and action are the two most important components of the production system in artificial intelligence. While the rule recognizes the condition, action uses the knowledge (coded behaviours) to deal with the condition. That’s why it is believed that production system is used across industries that predominantly utilize AI programmes to solve complex business problems.
What Are the Elements of the Production System?
Modern systems like production systems and artificial intelligence have many elements that help achieve efficiency and innovation. Like, different elements of data science that explain what data science is, production systems elements too do the same. In this section of the article, we will discuss different elements of a production system that help replace the workforce in labour-intensive work.
● Global Database
The primary infrastructure in the production system has all the knowledge stored. Therefore, a global database plays a significant role in ensuring that the production system completes all tasks efficiently. There are two types of Global databases: temporary and permanent.
As the name suggests, the temporary database stores information or knowledge that is significant in the current situation. Meanwhile, the permanent database contains information about fixed actions.
● A control system
The control system is one of the vital components of the production system in AI machines. They are the decision-makers who decide which production system is to be applied.
● Production rules
Production rules consist of various preconditions and postconditions used in a global database. They operate in the global database to provide a standard procedure to find solutions to different situations.
These elements of the production system make it function effectively in AI machines. In the next section of the article, we will learn about some of the features of the production system followed by an understanding of the classes of the production system.
What Are the Features of the Production System?
Some of the features of the production system are:
● Simplicity
The production system functions on the ‘If-Then’ structure which makes it a transparent application and easy to use for anyone. Moreover, this structure simplifies the knowledge representation, readability of production rules, etc., in production systems, making it easy for anyone to use.
● Knowledge-intensive
The production system stores only knowledge. It does not have any programming information or control. Furthermore, each production rule is written in English, making it easier for first-time users to access it.
● Modularity
The knowledge in the production system is added in pieces or blocks, making it easy to add, modify, and change without any repercussions.
● Modifiable
It is easy to modify production rules, making it a flexible computer algorithm.
What Are the Different Classes of Production Systems?
The production system has different classes that utilize production rules, databases, and knowledge differently. Below, we will be exploring these classes of the production system.
● Monotonic Production System
A monotonic production system is when two rules are simultaneously applied to the machine. Using one rule doesn’t affect the other rule in any way, which makes their co-existence easy.
● Partially Communicative Production System
In a partially communicative production system, when two or more rules are used to derive a result, any combination of the same rules produces the same result. Simply put, it means any permutation and combination of a set of rules will produce a similar result every time.
● Communicative Production System
A communicative production system is utilized for problems in which changes can reverse the outcome. That means the sequence of the operation is not critical in this class of production system.
● Non-monotonic Production System
This production system increases the problem-solving efficiency of the machine and eliminates previous records. However, since this production system does not allow backtracking the previous record, it is believed to be mostly used for solving ignorable problems.
Lastly, let us walk you through the advantages of the production system.
What Are the Benefits of the Production System?
- A smart artificial intelligence programme that imitates human cognition’s capability of solving problems.
- Easy-to-understand language and interface.
- It offers flexibility to add, delete, or modify rules according to your convenience.
- Separate knowledge base and control system.
- It can be easily applied to real life, especially in businesses, to solve complex problems.
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