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Commonsense reasoning

In artificial intelligence (AI), commonsense reasoning is a human-like ability to make presumptions about the type and essence of ordinary situations humans encounter every day.

Version
v1 · 2026-09-28 · History
Domain-specific #
8571
Domain group
Applied Sciences & Engineering
Origin domain
Computer Science & Software Engineering
Subdomains
Artificial Intelligence, Knowledge Representation → Computer Science & Software Engineering

Core Idea

Commonsense reasoning is treated here as the recurring computing and information systems identity summarized by this source-grounded definition: In artificial intelligence (AI), commonsense reasoning is a human-like ability to make presumptions about the type and essence of ordinary situations humans encounter every day. In artificial intelligence (AI), commonsense reasoning is a human-like ability to make presumptions about the type and essence of ordinary situations humans encounter every day. These assumptions include judgments about the nature of physical objects, taxonomic properties, and peoples' intentions.

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Everyday Sense for Computers

You know that if you let go of a ball it falls, and that if a friend is crying they are probably sad. Nobody has to tell you each time; it's just everyday sense. Commonsense reasoning is when a computer tries to have that same everyday sense, which is surprisingly hard for it.

Teaching Computers Common Sense

People know lots of everyday things without being taught them directly: heavy things fall, a dog is a kind of animal, people who say they are hungry want food. Commonsense reasoning, in artificial intelligence, is the ability to make these everyday guesses about ordinary situations. Computers often lack it, so they make strange mistakes people would never make. For example, a computer must know that 'the electrician is working' means doing a job, while 'the telephone is working' means it isn't broken.

Machine Everyday Inference

In artificial intelligence, commonsense reasoning is the human-like ability to make presumptions about ordinary, everyday situations: what kind of situation this is and what it is about. It covers judgments about physical objects (naive physics), categories and their properties, and people's intentions (folk psychology). For example, a translation system needs common sense to know that 'working' means 'laboring' for an electrician but 'functioning' for a telephone. Because AI systems often lack this background knowledge, they make mistakes that look bizarre to people, like being unsure who is advocating violence in a sentence about councilmen and demonstrators. One research effort, the commonsense knowledge problem, aims to build databases of the general knowledge most people are expected to have, in a form AI programs can use.

 

In AI, commonsense reasoning is the human-like capacity to make presumptions about the type and essence of ordinary everyday situations. It covers judgments about physical objects and their behavior (naive physics), taxonomic properties of categories, and people's intentions and behavior (folk psychology). Systems lacking it fail in ways that differ from human errors and can appear incomprehensible, for example misresolving an ambiguous pronoun whose referent a human settles using background knowledge about who is likely to advocate violence. It matters in natural-language tasks such as translation, where choosing the right sense of 'working' in 'the electrician is working' versus 'the telephone is working' depends on knowing what electricians and telephones are. The related commonsense knowledge problem is the effort to assemble the general knowledge most people are expected to have into a form accessible to AI programs that use natural language. The concept is specifically this presumptive, everyday-situation capacity in computing systems, not reasoning or knowledge representation in general.

Scope of Application

  • Commonsense reasoning problem. This enables even young children to easily make inferences like "If I roll this pen off a table, it will fall on the floor".

  • Commonsense reasoning problem. Humans also have a powerful mechanism of "folk psychology" that helps them to interpret natural-language sentences such as "The city councilmen refused the demonstrators a permit because they advocated violence".

  • Commonsense in intelligent tasks. For instance, when a machine is used to translate a text, problems of ambiguity arise, which could be easily resolved by attaining a concrete and true understanding of the context.

  • Commonsense in intelligent tasks. For example, in translating the sentences "The electrician is working" and "The telephone is working" into German, the machine translates correctly "working" in the means of "laboring" in the first one.

  • Commonsense in intelligent tasks. The machine has seen and read in the body of texts that the German words for "laboring" and "electrician" are frequently used in a combination and are found close together.

Clarity

A clear use of Commonsense reasoning names the carrier, the operative relation, and the conditions under which the source treats the identity as present. The minimal definition is In artificial intelligence (AI), commonsense reasoning is a human-like ability to make presumptions about the type and essence of ordinary situations humans encounter every day.

Manages Complexity

Commonsense reasoning compresses multiple computing and information systems details into a stable diagnostic relation. The source shows both the central mechanism—in 1961, Bar Hillel first discussed the need and significance of practical knowledge for natural language processing in the context of machine translation.—and the practical consequence—some movies contain scenes and moments that cannot be understood by simply matching memorized templates to images.

Abstract Reasoning

  1. Type the carrier. Identify the computing and information systems entities to which the claim applies.
  2. State the relation. Use the source-grounded identity: In artificial intelligence (AI), commonsense reasoning is a human-like ability to make presumptions about the type and essence of ordinary situations humans encounter every day.
  3. Check operation and conditions. Some ambiguities are resolved by using simple and easy to acquire rules.
  4. Demand recognition evidence.

Knowledge Transfer

Within the home domain. Knowledge about Commonsense reasoning transfers literally when a new case preserves the same carrier type, relation, and recognition test. This enables even young children to easily make inferences like "If I roll this pen off a table, it will fall on the floor". Humans also have a powerful mechanism of "folk psychology" that helps them to interpret natural-language sentences such as "The city councilmen refused the demonstrators a permit because they advocated violence". Beyond the home domain. No canonical parent is asserted for Commonsense reasoning.

Neighborhood in Abstraction Space

Commonsense reasoning sits in a sparse region of the domain-specific corpus (72nd percentile for distinctiveness): few abstractions share its structure, so a faithful description tends to retrieve it precisely.

Family — Unclustered & Miscellaneous (2551 abstractions)

Nearest neighbors

Computed from structural-signature embeddings · 2026-10-08