Reasoning Under Uncertainty in AI

Rajil TL
1 Min Read
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·         In a reasoning system, there are several types of uncertainty.

·         Reasoning under uncertainty research in AI is focused on uncertainty of truth value,in order to find the values other than True and False.

 

Nonmonotonic logics in AI

·         When new information is added to the system and if the truthfulness of a conclusion remains same , then the system is referred to as nonmonotonic. 

·         Lets understand with an example,

·         Birds typically swim 
Rhea is a bird
Tweety (presumably) flies

·         Commonsense is required in this type of reasoning and default rules are applied, if case specific information is not available.

·         The conclusion of non monotonic argument may be wrong. If Rhea is an ostrich, it is incorrect to conclude that Rhea flies. In this situation, the monotonic reasoning (that ostrich can run not fly) should be made available.

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Rajil TL is a SenseCentral contributor focused on tech, apps, tools, and product-building insights. He writes practical content for creators, founders, and learners—covering workflows, software strategies, and real-world implementation tips. His style is direct, structured, and action-oriented, often turning complex ideas into step-by-step guidance. He’s passionate about building useful digital products and sharing what works.

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