Tabling for Memoization Flashcards
7 cards from real Picat practice questions. Tap to flip, then mark Knew It or Still Learning โ missed cards come back until you master them.
Read the first 7 Tabling for Memoization flashcards as text
Which Picat directive marks a predicate so that its results are automatically cached?
Answer: table
The `table` directive placed before a predicate definition enables automatic memoization in Picat.
In Picat tabling, what happens when a tabled predicate is called with arguments it has already been called with?
Answer: The stored result is returned without re-executing the predicate body.
Tabling returns the cached result immediately, skipping redundant recomputation.
What is the primary algorithmic benefit of tabling in recursive Picat programs?
Answer: It converts exponential-time recursion into polynomial-time computation by caching subproblem results.
Tabling eliminates redundant recursive calls, reducing exponential blowups typical in naive recursion.
In a tabled Picat predicate with mode (+,+,-), what do the `-` signs indicate?
Answer: Output arguments whose values are stored in the table.
In tabling mode declarations, `-` denotes output (answer) arguments that the table records.
Which classic dynamic programming problem is most naturally expressed using Picat tabling?
Answer: Fibonacci sequence computation
Fibonacci has heavily overlapping subproblems that tabling eliminates, making it a textbook tabling example.
How does Picat's tabling handle a predicate that is called recursively before its result is fully computed (i.e., a loop)?
Answer: It uses iterative computation to accumulate answers incrementally until a fixpoint is reached.
Picat's tabling supports tabled logic programs with loops via iterative fixpoint computation.
What does the `table` declaration `table(+,+,min)` communicate to Picat's tabling system?
Answer: The third argument is an optimization objective to be minimized over all answers.
Mode `min` instructs the tabling system to keep only the answer with the smallest value for that argument, enabling optimal substructure computations.