Updated August 10, 2023
Introduction to Forward Chaining
In Artificial intelligence, we see forward chaining and backward chaining as very important parameters which help in its functionality.
Let’s first see what inference engines are where forward chaining is actually used.
Forward Chaining is a form of reasoning which uses atomic sentences that are present in the knowledge base, whereby applying inference rules on the given data for extracting more data in the forward direction is carried until the final goal is reached. When a decision is taken on the basis of the available data, such a process is known as forward chaining. It is also known as a data-driven approach.
Following are the properties of Forward chaining:
- The process moves from bottom to top.
- The conclusions are based upon unknown facts by making decisions from the initial stage whereby the final goal is reached
- Forward chaining is commonly utilized in production rule system and expert systems (for example CLIPS i.e., C Language Integrated Production System)
Process of Forward Chaining
There are several steps that are involved in order for forward chaining to be preceded. To make it simple to understand let us take an example.
It is established by the legal authorities that it is a crime for any American citizen to deal with the selling of weapons to any enemy Nation. Country A is an enemy nation of America which at present possesses some missiles. All these missiles have been sold to who this country by a colonel who happens to be an American citizen.
There are some facts give here:
- It is a crime for an American to sell weapons to an enemy of America
- Country A is the enemy of America
- A colonel of the army sells missiles to A
- Missiles are weapons
- The colonel is an American citizen
Conversion of the Fats
All the variables have to be traced out from the sentences. The following variables are:
- American
- Weapon
- Selling
- Hostile relations
- Criminal offense
- Colonel
- Missile
Step 1: In the first step of Forward chaining the sacks are analyzed. The sentences are segregated and the ones which do not have any implications are chosen. So, in the above sentence each of the following stands as a fact:
| America | A | Missile | Enemy | American (colonel) |
Step 2: we analyze that which are those facts that establish any kind of result.
Step 3: we have to check that each of the logical operators can be substituted by the available facts. If yes what substitute to reach the final goal.
In this approach, we can finally conclude that the colonel who is an American citizen has sold a missile which was a weapon to a country A which enemy to America proving making him legally a criminal.
For this system to be implemented there has to be a mechanism established the inference engine which is based on the rules which have been determined using forward chaining have to be fed into the working memory of the system in which the user can access this, input data and infer out results. The rules will be written in the knowledge base.
What is the use of Forward Chaining?
Forward chaining troops to be one of the most efficient tools which can be used when there is a single standing. Many possible endpoints can be made. The example given was a simplified one. But in complex situations, this algorithmically reduces the time very efficiently for coming to the best possible solution while implementing forward chaining.
Forward chaining mechanism can be used for simple devices such as the smoke alarm detector which directly indicates to the nearest fire station about the occurrence of a fire. The fire detector sensor will identify that a fire has occurred on the basis of two factors:
- The average room temperature near the sensor is greater than the average temperature of the building
- If there is smoke
- The density of the smoke
- The difference in the temperature (10 degrees or above)
Forward Chaining tool makes the machines that we use for daily purpose smart, the greater number of experiences is it was based on the situations the better it gets in responding.
Advantages and Disadvantages of Forward Chaining
Here are some of the advantages and disadvantages of forward chaining
Advantages
- Multiple variables can be felt in and multiple parallel conclusions can be drawn which is not seen in backward chaining
- Chaining proves to be the best tool to be used when the hypothesis to be taken is not very clear to the user as he needs to see what are the conclusions that can be drawn out of the situation provided.
Disadvantages
- The major disadvantage of Forwarding chaining is the amount of time it takes for eliminating, structuring and synchronizing the data which has been given after segregating it into various variables.
- The hypothesis for forward chaining is not that clear compared to backward chaining as the latter is more goal-driven, reducing the amount of time taken to come to conclusions very efficiently
Conclusion
The forward-chaining tool which is utilized in expert systems helps in emulating the decision-making ability which is possessed by humans to be replicated in Computer-Based systems. Using this mechanism, the computers are able to make logical decisions on the basis of and or and else loops which give rise to simple objective decisions that are implemented in the form of action.
Do a very simple tool in the large Horizon of AI it serves to be one of the most efficient methodologies and still implemented by the expert systems of NASA combining the paradigm of procedural programming and logic-based object-oriented languages. This tool thereby extensively reduces the monologue redundant tasks which have to be done by a human being and I replaced by computer systems.
Thus, humans are involved in two processes where the Machines cannot give a logical solution making the best utilization of resources and outsourcing the work which has less logic-based value to machines.
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This has been a guide to Forward Chaining. Here we discuss their process, conversion, uses, advantages, and disadvantages of forward chaining. You may also have a look at the following articles to learn more –
