Common Sense Knowledge

A Common Sense Knowledge is a semantic knowledge of common sense beliefs.

• Example(s):
  • On Earth, something unsupported typically falls due to gravity
• Counter-Example(s):
  • Domain-Specific Knowledge.
  • Academic Knowledge.
• See: Knowledge Representation, Upper Ontology, AI-Complete, Machine Translation, Object Recognition.

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References

2015

• (Wikipedia, 2015) ⇒ http://en.wikipedia.org/wiki/Commonsense_knowledge_(artificial_intelligence) Retrieved:2015-2-8.
  • In artificial intelligence research, commonsense knowledge is the collection of facts and information that an ordinary person is expected to know. The commonsense knowledge problem is the ongoing project in the field of knowledge representation (a sub-field of artificial intelligence) to create a commonsense knowledge base: a database containing all the general knowledge that most people possess, represented in a way that it is available to artificial intelligence programs that use natural language or make inferences about the ordinary world. Such a database is a type of ontology of which the most general are called upper ontologies.

    The problem is considered to be among the hardest in all of AI research because the breadth and detail of commonsense knowledge is enormous. Any task that requires commonsense knowledge is considered AI-complete: to be done as well as a human being does it, it requires the machine to appear as intelligent as a human being. These tasks include machine translation, object recognition, text mining and many others. To do these tasks perfectly, the machine simply has to know what the text is talking about or what objects it may be looking at, and this is impossible in general unless the machine is familiar with all the same concepts that an ordinary person is familiar with.

    Information in a commonsense knowledge base may include, but is not limited to, the following:

    • An ontology of classes and individuals
    • Parts and materials of objects
    • Properties of objects (such as color and size)
    • Functions and uses of objects
    • Locations of objects and layouts of locations
    • Locations of actions and events
    • Durations of actions and events
    • Preconditions of actions and events
    • Effects (postconditions) of actions and events
    • Subjects and objects of actions
    • Behaviors of devices
    • Stereotypical situations or scripts
    • Human goals and needs
    • Emotions
    • Plans and strategies
    • Story themes
    • Contexts

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2022

• (Wikipedia, 2022) ⇒ https://en.wikipedia.org/wiki/Commonsense_knowledge_(artificial_intelligence) Retrieved:2022-8-8.
  • In artificial intelligence research, commonsense knowledge consists of facts about the everyday world, such as "Lemons are sour", that all humans are expected to know. It is currently an unsolved problem in Artificial General Intelligence. The first AI program to address common sense knowledge was Advice Taker in 1959 by John McCarthy. Commonsense knowledge can underpin a commonsense reasoning process, to attempt inferences such as "You might bake a cake because you want people to eat the cake." A natural language processing process can be attached to the commonsense knowledge base to allow the knowledge base to attempt to answer questions about the world. Common sense knowledge also helps to solve problems in the face of incomplete information. Using widely held beliefs about everyday objects, or common sense knowledge, AI systems make common sense assumptions or default assumptions about the unknown similar to the way people do. In an AI system or in English, this is expressed as "Normally P holds", "Usually P" or "Typically P so Assume P". For example, if we know the fact "Tweety is a bird", because we know the commonly held belief about birds, "typically birds fly," without knowing anything else about Tweety, we may reasonably assume the fact that "Tweety can fly." As more knowledge of the world is discovered or learned over time, the AI system can revise its assumptions about Tweety using a truth maintenance process. If we later learn that "Tweety is a penguin" then truth maintenance revises this assumption because we also know "penguins do not fly".

2022

• (Wikipedia, 2022) ⇒ https://en.wikipedia.org/wiki/Commonsense_knowledge_(artificial_intelligence) Retrieved:2022-8-8.
  • In artificial intelligence research, commonsense knowledge consists of facts about the everyday world, such as "Lemons are sour", that all humans are expected to know. It is currently an unsolved problem in Artificial General Intelligence. The first AI program to address common sense knowledge was Advice Taker in 1959 by John McCarthy. Commonsense knowledge can underpin a commonsense reasoning process, to attempt inferences such as "You might bake a cake because you want people to eat the cake." A natural language processing process can be attached to the commonsense knowledge base to allow the knowledge base to attempt to answer questions about the world. Common sense knowledge also helps to solve problems in the face of incomplete information. Using widely held beliefs about everyday objects, or common sense knowledge, AI systems make common sense assumptions or default assumptions about the unknown similar to the way people do. In an AI system or in English, this is expressed as "Normally P holds", "Usually P" or "Typically P so Assume P". For example, if we know the fact "Tweety is a bird", because we know the commonly held belief about birds, "typically birds fly," without knowing anything else about Tweety, we may reasonably assume the fact that "Tweety can fly." As more knowledge of the world is discovered or learned over time, the AI system can revise its assumptions about Tweety using a truth maintenance process. If we later learn that "Tweety is a penguin" then truth maintenance revises this assumption because we also know "penguins do not fly".