### Reasoning

The action of thinking about something logical is called reasoning. The reasoning is the mental process of deriving logical conclusion and making predictions from available knowledge, facts, and beliefs. Or we can say, "Reasoning is a way to infer facts from existing data." It is a general process of thinking rationally, to find valid conclusions.

In artificial intelligence, the reasoning is essential so that the machine can also think rationally as a human brain, and can perform like a human.

#### Types of Reasonings

In artificial intelligence, reasoning can be divided into the following categories:

• Deductive reasoning:

• • Deductive reasoning is deducing new information from logically related known information. It is the form of valid reasoning, which means the argument's conclusion must be true when the premises are true.
• • Deductive reasoning is a type of propositional logic in AI, and it requires various rules and facts. It is sometimes referred to as top-down reasoning, and contradictory to inductive reasoning.
• • In deductive reasoning, the truth of the premises guarantees the truth of the conclusion.

Example:

• Premise-1: All animal eats food.
• Premise-2: Human is an animal.
• Conclusion: Human eats food.

• Inductive reasoning:

• • Inductive reasoning is a form of reasoning to arrive at a conclusion using limited sets of facts by the process of generalization. It starts with the series of specific facts or data and reaches to a general statement or conclusion.
• • Inductive reasoning is a type of propositional logic, which is also known as cause-effect reasoning or bottom-up reasoning.
• • In inductive reasoning, we use historical data or various premises to generate a generic rule, for which premises support the conclusion.
• • In inductive reasoning, premises provide probable supports to the conclusion, so the truth of premises does not guarantee the truth of the conclusion.

Example:

• Premise: All of the pigeons we have seen in the zoo are white.
• Conclusion: Therefore, we can expect all the pigeons to be white.

• Abductive reasoning:

• • Abductive reasoning is a form of logical reasoning which starts with single or multiple observations then seeks to find the most likely explanation or conclusion for the observation.
• • Abductive reasoning is a form of logical reasoning which starts with single or multiple observations then seeks to find the most likely explanation or conclusion for the observation.

Example:

• Implication: Field is wet if it is raining
• Axiom: Field is wet.
• Conclusion: It is raining.

• Common Sense Reasoning:

• • Common sense reasoning is an informal form of reasoning, which can be gained through experiences.
• • Common Sense reasoning simulates the human ability to make presumptions about events which occurs on every day.
• • It relies on good judgment rather than exact logic and operates on heuristic knowledge and heuristic rules.

Example:

• One person can be at one place at a time.
• If I put my hand in a fire, then it will burn.

The above two statements are the examples of common-sense reasoning which a human mind can easily understand and assume.

• Monotonic Reasoning:

• • In monotonic reasoning, once the conclusion is taken, then it will remain the same even if we add some other information to existing information in our knowledge base. In monotonic reasoning, adding knowledge does not decrease the set of prepositions that can be derived.
• • To solve monotonic problems, we can derive the valid conclusion from the available facts only, and it will not be affected by new facts.
• • Monotonic reasoning is not useful for the real-time systems, as in real time, facts get changed, so we cannot use monotonic reasoning.
• • Monotonic reasoning is used in conventional reasoning systems, and a logic-based system is monotonic.
• • Any theorem proving is an example of monotonic reasoning.

Example:

• Sun rises in the est.

It is a true fact, and it cannot be changed even if we add another sentence in knowledge base like, "The earth revolves around the sun " Or "Moon revolves around the earth," etc.

• Non-monotonic Reasoning:

• • In Non-monotonic reasoning, some conclusions may be invalidated if we add some more information to our knowledge base.
• • Logic will be said as non-monotonic if some conclusions can be invalidated by adding more knowledge into our knowledge base.
• • Non-monotonic reasoning deals with incomplete and uncertain models.
• • "Human perceptions for various things in daily life, "is a general example of non-monotonic reasoning.

Example:Let suppose the knowledge base contains the following knowledge:

• Birds can fly
• Ostrich cannot fly
• Struthio camelus is a birdS

So, from the above sentences, we can conclude that Struthio camelus can fly.

However, if we add one another sentence into knowledge base " Struthio camelus is an Ostrich", which concludes " Struthio camelus cannot fly", so it invalidates the above conclusion.

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