Answers.Body: <p>Mostly because traditional "knowledge based systems" are based purely on deductive logic and that's just the way deduction works.  It only deals with what consequences <em>must</em> follow from the premises.  Traditionally these systems didn't deal with probabilistic knowledge or other less strict forms of reasoning, like abduction.  </p>
  
  <p>That said, it is possible to build a knowledge based system that includes probabilistic reasoning, and other reasoning systems (like abduction). </p>
  
  <p>I'll add some more on that point when I have a little more time.</p>
  
Answers.ContentLicense: CC BY-SA 3.0
Answers.CreationDate: 2017-08-24T19:26:18.933Z
Answers.LastActivityDate: 2017-08-24T19:26:18.933Z
Answers.UserDisplayName: mindcrime
Body: <p>According to Russell and Norvig, a knowledge-based agent will only add a sentence to its knowledge base if it <em>follows logically</em> from what it previously knows, or directly observes. To <em>follow logically</em> essentially means that if the premises are true, then the conclusions are guaranteed to be true. So the agent will only add the sentence if it 100% sure the sentence is true.</p>
  
  <p>Is this hyperskepticism in logic justified? Couldn't the agent be more efficient if it added a sentence if it were 99% sure it were true? It could potentially add a lot more true sentences, and only occasionally add false ones. There would need to be a mechanism for unlearning sentences, but as long as the vast majority of sentences added are true, why couldn't that be done?</p>
  
  <p>I essentially asked this question <a href="https://en.wikipedia.org/wiki/Wikipedia:Reference_desk/Miscellaneous#.22Proof.22_of_the_principle_of_skepticism.3F" rel="noreferrer">here</a>, and someone suggested that I post it here.</p>
  
Comments.ContentLicense: CC BY-SA 3.0
Comments.CreationDate: 2017-08-24T18:26:46.410Z
Comments.Text: Great question.  (Please link the Russell and Norvig if you get a chance.)  PS- Welcome to AI!
Comments.UserDisplayName: DukeZhou
Tags: <logic>
Title: Why do knowledge-based agents only add a sentence to the knowledge base when it is 100% sure the sentence is true?
UserDisplayName: Peter
ThreadText: # Why do knowledge-based agents only add a sentence to the knowledge base when it is 100% sure the sentence is true?
  
  (Asked by: username_0 on 2017-08-24)
  
  According to Russell and Norvig, a knowledge-based agent will only add a sentence to its knowledge base if it *follows logically* from what it previously knows, or directly observes. To *follow logically* essentially means that if the premises are true, then the conclusions are guaranteed to be true. So the agent will only add the sentence if it 100% sure the sentence is true.
  
  Is this hyperskepticism in logic justified? Couldn't the agent be more efficient if it added a sentence if it were 99% sure it were true? It could potentially add a lot more true sentences, and only occasionally add false ones. There would need to be a mechanism for unlearning sentences, but as long as the vast majority of sentences added are true, why couldn't that be done?
  
  I essentially asked this question [here](https://en.wikipedia.org/wiki/Wikipedia:Reference_desk/Miscellaneous#.22Proof.22_of_the_principle_of_skepticism.3F), and someone suggested that I post it here.
  
  **Tags:** logic
  > **Comments:**
  > **username_1**: Great question.  (Please link the Russell and Norvig if you get a chance.)  PS- Welcome to AI!  
  
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  ## 1 answers
  
  ### Answer by username_2 on 2017-08-24. Score: 4
  
  Mostly because traditional "knowledge based systems" are based purely on deductive logic and that's just the way deduction works. It only deals with what consequences *must* follow from the premises. Traditionally these systems didn't deal with probabilistic knowledge or other less strict forms of reasoning, like abduction.
  
  That said, it is possible to build a knowledge based system that includes probabilistic reasoning, and other reasoning systems (like abduction).
  
  I'll add some more on that point when I have a little more time.
  
  
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