What You Will Learn
- 1 What Is a Production System?
- 2 Components of Production System
- 3 What are the Features of a Production System?
- 4 Classifications of Production Systems
- 5 Advantages of Production Systems In AI
- 6 Disadvantages of Production Systems In AI
- 7 Example of Production System in Artificial Intelligence
What Is a Production System?
Production system or production rule system may be a computer virus typically wont to provide some sort of AI, which consists primarily of a group of rules about behavior but it also includes the mechanism necessary to follow those rules because the system responds to states of the planet.
Example of Production System:
- IF the initial state may be a goal state THEN quit.
- The major components production system is of an AI
i. a worldwide database
ii. a group of production rules and
iii. an impact system
Components of Production System
The major components of the Production System in AI:
The worldwide database is the central arrangement employed by the assembly system in AI.
Set of Production Rules:
The assembly rules operate the worldwide database. Each rule usually features a precondition that’s either satisfied or not by the worldwide database. If the precondition is satisfied, the rule is typically be applied. The appliance of the rule changes the database.
A Control System:
A Control System: The system then chooses that applicable rule ought to be applied and ceases computation once a termination condition on the information is satisfied.
What are the Features of a Production System?
- Simplicity: Thanks to the utilization of the IF-THEN structure, each sentence is exclusive within the production system. This uniqueness makes the knowledge representation simple to reinforce the readability of the assembly rules.
- Modularity: The knowledge available is coded in discrete pieces by the assembly system, which makes it easy to feature, modify, or delete the knowledge with none side effects.
- Modifiability: This feature allows for the modification of the assembly rules. The principles are first defined within the skeletal form then modified to suit an application.
- Knowledge-intensive: because the name suggests, the system only stores knowledge. All the principles are written in English. This sort of representation solves the semantics problem.
Classifications of Production Systems
The production system describes the operations which will be performed during a look for an answer to the matter. These are four classification
1. A monotonic production system
2. A non-monotonic production system
3. A partially commutative production system
4. A commutative production system.
Monotonic Production System:
These systems area unit vital for a person implementation viewpoint as a result of they’re going to be enforced while not the ability to go back to previous states once it’s discovered that associate incorrect path was followed.
Partially Commutative Production System:
It’s a sort of production system throughout that the appliance of a sequence of rules transforms state X into state Y, then any permutation of those rules that is allowable additionally transforms state x into state Y. Theorem proving falls below the monotonic part communicative system.
Non-Monotonic Production Systems:
It’s is beneficial for finding ignorable issues. These systems area unit is vital for man implementation viewpoint as a result of they’re going to be enforced while not the ability to go back to previous states once it’s discovered that associate incorrect path was followed.
It’s typically helpful for issues throughout that changes occur however area unit typically reversed and through that the order of operation is not crucial for example the, eight puzzle drawbacks.
Advantages of Production Systems In AI
- Provides excellent tools for structuring AI programs
- The system is very modular because individual rules are often added, removed, or modified independently.
- Expressed in natural form.
- Separation of data and Control – Recognises Act Cycle.
- A natural mapping onto state-space research – data or goal-drive.
- The modularity of production rules.
- The system uses pattern directed control which is more flexible than algorithmic control.
- Provides opportunities for heuristic control of search.
- Tracing and Explanation Simple Control, Informative rules.
- Language Independence.
- A plausible model of human problem solving -SOAR, ACT.
- A great way to model the state-driven nature of intelligent machines.
- Quite helpful in real-time in the environment and applications.
Disadvantages of Production Systems In AI
- It’s very difficult to analyze the flow of control within a production system.
- It describes the operations which will performed during a look for an answer to the matter. They will be classified as follows.
- There is an absence of learning thanks to a rule-based production system that doesn’t store the results of the matter for future use.
- The rules within the production system shouldn’t have any sort of conflict resolution as when a replacement rule is added to the database it should make sure that it doesn’t have any conflict with any existing rules.
Example of Production System in Artificial Intelligence
We have two jugs of capacity 5l and 3l (liter), and a faucet with an endless supply of water. the target is to get 4 liters exactly within the 5-liter jug with the minimum steps possible.
1: Fill the 5-liter jug from a tap
2: Empty the 5-liter jug
3: Fill the three-liter jug from a tap
4: Empty the three-liter jug
5: Then, empty the three-liter jug to five-liter
6: Empty the 5-liter jug to three-liter
7: Pour water from 3 liters to five-liter
8: Pour water from 5 liters to three liters but don’t empty
1,8,4,6,1,8 or 3,5,3,7,2,5,3,5;
It is possible to possess other solutions also but these are the shortest and therefore the 1st sequence should be chosen because it has the minimum number of steps.
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