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A non-monotonic logic is a formal logic whose entailment relation is not monotonic.In other words, non-monotonic logics are devised to capture and represent defeasible inferences, i.e., a kind of inference in which reasoners draw tentative conclusions, enabling reasoners to retract their conclusion(s) based on further evidence. [1]
Other, non-probabilistic extensions to first-order logic to support were also tried. For example, non-monotonic reasoning could be used with truth maintenance systems. A truth maintenance system tracked assumptions and justifications for all inferences. It allowed inferences to be withdrawn when assumptions were found out to be incorrect or a ...
Non-monotonic reasoning. Non-monotonic reasoning allows various kinds of hypothetical reasoning. The system associates facts asserted with the rules and facts used to justify them and as those facts change updates the dependent knowledge as well. In rule based systems this capability is known as a truth maintenance system. [25] Expressive ...
Default logic is a non-monotonic logic proposed by Raymond Reiter to formalize reasoning with default assumptions.. Default logic can express facts like “by default, something is true”; by contrast, standard logic can only express that something is true or that something is false.
[citation needed] Extensive work has also been done in reasoning by analogy using induction and abduction. [1] Other important topics include reasoning under uncertainty and non-monotonic reasoning. An important part of the uncertainty field is that of argumentation, where further constraints of minimality and consistency are applied on top of ...
OpenAI introduced o3-mini, a cost-efficient reasoning AI model, on Friday. The release comes as DeepSeek's R1 model shakes up the tech industry. OpenAI said the o3-mini excels in science, math ...
Later symbolic AI work after the 1980's incorporated more robust approaches to open-ended domains such as probabilistic reasoning, non-monotonic reasoning, and machine learning. Currently, most AI researchers [citation needed] believe deep learning , and more likely, a synthesis of neural and symbolic approaches ( neuro-symbolic AI ), will be ...
As well as logical or bitwise complement, systems may support existential forms of strong and weak negation including negation-as-failure and 'inflationary' negation (negation of non-ground atoms). Different reasoning systems may support monotonic or non-monotonic reasoning, stratification and other logical techniques.