Knowledge-Based Agents: Inference, Soundness, and Completeness

 
Knowledge-Based
Agents
 
Part 3: wrap up
 
Some material adopted from notes by 
Andreas Geyer-Schulz and Chuck Dyer
 
Inference, Soundness, Completeness
 
KB 
i 
α = sentence α can be derived from 
KB
by procedure 
i
Soundness:
 
i
 is sound if whenever 
KB 
i 
α, it
is also true that 
KB
 α
Completeness:
 
i
 is complete if whenever
KB
 α, it is also true that 
KB 
i 
α
 
Preview: 
first-order logic 
is expressive
enough to say almost anything of interest
and has a 
sound
 and 
complete
 inference
procedure
 
Soundness and completeness
 
A 
sound
 inference method derives only
entailed sentences
Analogous to the property of 
completeness
in search, a 
complete
 inference method can
derive any sentence that is entailed
 
No independent access to the world
 
Reasoning agents often gets knowledge about facts
of the world as a sequence of logical sentences and
must draw conclusions only from them w/o
independent access to world
Thus, it is very important that the agents’
 reasoning
is sound!
 
Summary
 
Intelligent agents need knowledge about world for good
decisions
Agent’s knowledge stored in a knowledge base (KB) as
sentences
 in a knowledge representation (KR) language
 Knowledge-based agents needs a 
KB
 & 
inference
mechanism
. They store sentences in KB, infer new
sentences & use them to 
deduce
 which actions to take
A 
representation language
 defined by its syntax &
semantics, which specify structure of sentences & how
they relate to facts of the world
Interpretation
 of a sentence is fact to which it refers. If
fact is part of the actual world, then the sentence is true
 
Fin
 
6
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Inference, soundness, and completeness are crucial concepts in knowledge-based agents. First-order logic allows for expressive statements and has sound and complete inference procedures. Soundness ensures derived sentences are true, while completeness guarantees all entailed sentences are derived. Agents rely on logical sentences for reasoning without direct access to the world, emphasizing the importance of sound reasoning. Knowledge-based agents store information in a knowledge base, utilize an inference mechanism, and make decisions based on inferred actions using a representation language that defines sentence structure and semantics.

  • Knowledge-based agents
  • Inference
  • Soundness
  • Completeness
  • First-order logic

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  1. Knowledge-Based Agents Part 3: wrap up Some material adopted from notes by Andreas Geyer-Schulz and Chuck Dyer

  2. Inference, Soundness, Completeness KB i = sentence can be derived from KB by procedure i Soundness:i is sound if whenever KB i , it is also true that KB Completeness:i is complete if whenever KB , it is also true that KB i Preview: first-order logic is expressive enough to say almost anything of interest and has a sound and complete inference procedure

  3. Soundness and completeness A sound inference method derives only entailed sentences Analogous to the property of completeness in search, a complete inference method can derive any sentence that is entailed

  4. No independent access to the world Reasoning agents often gets knowledge about facts of the world as a sequence of logical sentences and must draw conclusions only from them w/o independent access to world Thus, it is very important that the agents reasoning is sound!

  5. Summary Intelligent agents need knowledge about world for good decisions Agent s knowledge stored in a knowledge base (KB) as sentences in a knowledge representation (KR) language Knowledge-based agents needs a KB & inference mechanism. They store sentences in KB, infer new sentences & use them to deduce which actions to take A representation language defined by its syntax & semantics, which specify structure of sentences & how they relate to facts of the world Interpretation of a sentence is fact to which it refers. If fact is part of the actual world, then the sentence is true

  6. Fin Fin 6

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