What is backwards chaining

Expert systems are intelligent computer systems or programs that predate the AI-powered machines and smart devices that we know today. An expert system consists of a user interface , an inference engine that scans available facts from a knowledge base, and a knowledge base — a library where valuable data from experts is stored. Expert systems were built to provide answers akin to human experts in a field of study, hence the name. Every noun, verb, adjective, adverb, pronoun, preposition, and conjunction in the sentence must have a predicate which tells what the subject is or does.

Word senses can be added to logic forms to clarify semantics. Logic forms are utilized in some natural language processing NLP techniques, such as question answering and inferencing for database and quality assurance QA systems. Backward chaining starts with goals or a hypothesis and works backward from the consequent to the antecedent to see if any data supports the consequent.

An inference engine searches inference rules until it finds one with a consequent i. Backward and forward chaining are methods of reasoning that exist in the Expert System Domain of artificial intelligence.

This article provides an overview of these techniques, and how they work. By the end of the article, readers will have learned real life examples of how backward and forward chaining are applied in artificial intelligence. A brief overview of an expert system can help us gain more insights on the origin of backward and forward chaining in artificial intelligence.

An expert system is a computer application that uses rules, approaches, and facts to provide solutions to complex problems. MYCIN uses the backward chaining technique to diagnose bacterial infections. There are three components in an expert system: user interface, inference engine, and knowledge base. The user interface enables users of the system to interact with the expert system. High-quality and domain-specific knowledge is stored in the knowledge base.

Backward and forward chaining stem from the inference engine component. This is a component in which logical rules are applied to the knowledge base to get new information or make a decision. The backward and forward chaining techniques are used by the inference engine as strategies for proposing solutions or deducing information in the expert system. Image Source: Tutorials Point.

Forward chaining is a method of reasoning in artificial intelligence in which inference rules are applied to existing data to extract additional data until an endpoint goal is achieved. In this type of chaining, the inference engine starts by evaluating existing facts, derivations, and conditions before deducing new information.

An endpoint goal is achieved through the manipulation of knowledge that exists in the knowledge base. Deducing the chemical structure starts by finding the number of atoms in every molecule. The mass spectrum of the sample is then used to establish the arrangement of the atoms. We can summarize these steps as follows. In this example, the identification of the chemical structure is the endpoint.

There are two elements in the generator: a synthesiser and structural enumerator. The synthesiser plays the role of producing the mass spectrum. When teaching a new skill we often start at the beginning. This can be challenging for children sometimes as they get frustrated. You can give your child a sense of achievement by using the backward chaining technique. Backward chaining is particularly useful when learning self-care skills like dressing.

It can also be helpful when teaching younger children. It is also useful when someone is having difficulty learning new skills. So what is backward chaining? You start by breaking the task down into small steps. You teach your child the last step first, working backwards from the goal. You complete all the steps except the last one.

You get your child to practice the final step. Your child will enjoy the success that comes from completing a task. Once your child can do the last step you complete all the steps except for the last two. You teach your child the second from the last step and they then complete the last step themselves. You can continue to do this with almost any task as long as you can break it down into smaller steps.

In summary, providing your child with the opportunity to complete tasks independently in a structured manner should increase his independence throughout life. Categories: Occupational Therapy , Trisomy Teaching your child to do the last step in a multi-step process can build self confidence and skill retention.

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