Gundlagen der Künstlichen Intelligenz at TU München

Flashcards and summaries for Gundlagen der Künstlichen Intelligenz at the TU München

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Exemplary flashcards for Gundlagen der Künstlichen Intelligenz at the TU München on StudySmarter:

When is a variable arc consistent ?

Exemplary flashcards for Gundlagen der Künstlichen Intelligenz at the TU München on StudySmarter:

What does Interference mean

Exemplary flashcards for Gundlagen der Künstlichen Intelligenz at the TU München on StudySmarter:

What is Direct arc consistency ?

Exemplary flashcards for Gundlagen der Künstlichen Intelligenz at the TU München on StudySmarter:

When is a CSP-graph arc consistent?

Exemplary flashcards for Gundlagen der Künstlichen Intelligenz at the TU München on StudySmarter:

which possibilites are there to gain knowledge?

Exemplary flashcards for Gundlagen der Künstlichen Intelligenz at the TU München on StudySmarter:

when to use theorem proving?
which concepts are required?

Exemplary flashcards for Gundlagen der Künstlichen Intelligenz at the TU München on StudySmarter:

What is Conditioning ?

[Context: Nearly tree-structured CSPs]

Exemplary flashcards for Gundlagen der Künstlichen Intelligenz at the TU München on StudySmarter:

What is the definition of Syntax, Semantics and Model?

Exemplary flashcards for Gundlagen der Künstlichen Intelligenz at the TU München on StudySmarter:

What are the main steps of the Arc-Consistency-Algorithm?

Exemplary flashcards for Gundlagen der Künstlichen Intelligenz at the TU München on StudySmarter:

What are the main steps of the forward checking consistency algorithm?

Exemplary flashcards for Gundlagen der Künstlichen Intelligenz at the TU München on StudySmarter:

What is the Least Constraining Value heuristic

Exemplary flashcards for Gundlagen der Künstlichen Intelligenz at the TU München on StudySmarter:

What's the benefit of a fail-first variable selection like MRV

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Exemplary flashcards for Gundlagen der Künstlichen Intelligenz at the TU München on StudySmarter:

Gundlagen der Künstlichen Intelligenz

When is a variable arc consistent ?

Consistency between X_k and X_a:

  • Every Value in domain D_k has value in D_a, that satisfy constraint in arc (X_k,X_a)

Arc consistency is not commutative!

Gundlagen der Künstlichen Intelligenz

What does Interference mean

Draw (logical, new) conclusions from given premises

Gundlagen der Künstlichen Intelligenz

What is Direct arc consistency ?

  • Only feasible if there are no loops in the graph
  • A graph is direct arc consistent iif
    • every X_i is arc-consistent with each directly following neighbor j > i

Gundlagen der Künstlichen Intelligenz

When is a CSP-graph arc consistent?

Every variable is arc-consistent with every other variable

Gundlagen der Künstlichen Intelligenz

which possibilites are there to gain knowledge?
  • inference
  • declarative approach
  • perception

levels agents can be viewed at:

  • knowledge level
  • implementation level

Gundlagen der Künstlichen Intelligenz

when to use theorem proving?
which concepts are required?

if the number of models are large but the lengths of proof is short

  • logical equivalence: a implies b and b implies a
  • validity: sentence is valid if its true in all models, also known as tautologies
  • satisfiability: if a sentence is true in some model

Gundlagen der Künstlichen Intelligenz

What is Conditioning ?

[Context: Nearly tree-structured CSPs]

For graph with loops:

  • Remove subset S, such that the graph becomes a tree
    • fix S to specific value
    • update neighbors
    • reorder CSP as tree

Gundlagen der Künstlichen Intelligenz

What is the definition of Syntax, Semantics and Model?

Syntax: how correct sentences are formed

Semantics: defines meaning of sentences

Models: models are instances which evaluate sentences to true or false

Gundlagen der Künstlichen Intelligenz

What are the main steps of the Arc-Consistency-Algorithm?

  • Init FIFO queue
    • as pre-processing: all arcs
    • as interference: All neighboring arcs of assigned var
  • queue.pop()
    • remove inconsistent vals
      • if none: repeat queue.pop()
      • if some: Check if domain is empty
        • yes: backtrack
        • no: add all neighbors of this Var to queue [except: “partner” of current arc]
          • repeat queue.pop()

Gundlagen der Künstlichen Intelligenz

What are the main steps of the forward checking consistency algorithm?

  • Assign Value to Variable
  • Check all neighbors of that Var
    • Remove inconsistent Values of their domains
      • (no assignment happens here)
  • Check if a domain is empty
    • No: assign next var
    • Yes: backtrack

Gundlagen der Künstlichen Intelligenz

What is the Least Constraining Value heuristic

  • Heuristic for choosing order of values
  • Choose value that rules out fewest choices of neighbors
  • “Fail-last”-approach

Gundlagen der Künstlichen Intelligenz

What's the benefit of a fail-first variable selection like MRV

Prunes the search-tree for first iterations

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