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What is non-monotonic reasoning in Computational Intelligence?

What is non-monotonic reasoning in Computational Intelligence?

A logic is non-monotonic if some conclusions can be invalidated by adding more knowledge. The logic of definite clauses with negation as failure is non-monotonic.

What is monotonic in AI?

Monotonicity in artificial intelligence (AI) can refer to monotonic classification or monotonic reasoning. Monotonic classification is a mathematical property of an AI model closely related to the concept of a monotonic function. Monotonic reasoning is a form of reasoning that can underlie the AI system’s logic.

What is non-monotonic?

Definitions of nonmonotonic. adjective. not monotonic. Antonyms: monotone, monotonic. of a sequence or function; consistently increasing and never decreasing or consistently decreasing and never increasing in value.

What is the difference between non-monotonic reasoning and TMS?

Truth Maintenance System (TMS): The logics are known as monotonic logics. The form of reasoning referred to above, on the other hand, is non-monotonic. New facts become known which can contradict and can invalidate the old knowledge.

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What is monotonic and non-monotonic?

Monotonic means something that does not vary or change. Non-Monotonic means something which can vary according to the situation or condition.

What is non-monotonic knowledge?

A non-monotonic logic is a formal logic whose conclusion relation is not monotonic. In other words, non-monotonic logics are devised to capture and represent defeasible inferences (cf. Intuitively, monotonicity indicates that learning a new piece of knowledge cannot reduce the set of what is known.

What is non-monotonic reasoning give an example?

Non-monotonic Reasoning 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. Penguins cannot fly.

What is non-monotonic reasoning explain the logics used for non-monotonic reasoning?

In other words, non-monotonic logics are devised to capture and represent defeasible inferences (cf. defeasible reasoning), i.e., a kind of inference in which reasoners draw tentative conclusions, enabling reasoners to retract their conclusion(s) based on further evidence.

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Is probabilistic reasoning monotonic or non-monotonic?

Generally and vaguely, I take them to embody what I shall call probabilistic inference. This form of inference is clearly non-monotonic. Relatively few people have taken this form of inference, based on high probability, to serve as a foundation for non-monotonic logic or for a logical or defeasible inference.

What is circumscription in artificial intelligence?

Circumscription is a non-monotonic logic created by John McCarthy to formalize the common sense assumption that things are as expected unless otherwise specified. Circumscription was later used by McCarthy in an attempt to solve the frame problem.

What is antonym of monotonic?

Antonyms: nonmonotonic, modulated. Synonyms: plane, savourless, flavorless, categoric, matt, humdrum, insipid, level, compressed, flat, unconditional, matted, vapid, categorical, monotonous, two-dimensional, matte, monotone, savorless, prostrate, bland, mat, flavourless.

What is a non-monotonic logic?

A logic is non-monotonicifsome conclusions can be invalidated by adding more knowledge. The logic of definite clauses with negation as failure is non-monotonic. Non-monotonic reasoning is useful for representing defaults. A defaultisa rule that can be used unless it overridden by an exception.

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Can we use non-monotonic reasoning in robot navigation?

For real-world systems such as Robot navigation, we can use non-monotonic reasoning. In Non-monotonic reasoning, we can choose probabilistic facts or can make assumptions. In non-monotonic reasoning, the old facts may be invalidated by adding new sentences.

Why can’t we use monotonic reasoning in the real world?

In monotonic reasoning, each old proof will always remain valid. If we deduce some facts from available facts, then it will remain valid for always. We cannot represent the real world scenarios using Monotonic reasoning. Hypothesis knowledge cannot be expressed with monotonic reasoning, which means facts should be true.

What are the advantages of non-monotonic learning?

2.greater choice in learning strategies. Non-monotonic learning is when an agent may learn the new knowledge that contradicts what it already known or existing. So it replaces the old knowledge with new if it believes there is sufficient reason to do so. The advantages of non-monotonic learning are: