Picat The Planner Module 4

Question 1

What optional predicate can be defined to enable informed (heuristic-guided) search in Picat's planner?

Accepted Answer

heuristic/2

Answer

Defining `heuristic(State, H)` provides the planner with a cost-to-goal estimate H, enabling A*-style best-first search.

Question 2

For `heuristic/2` to guarantee optimal solutions, what property must the heuristic value H satisfy?

Accepted Answer

H must never overestimate the true remaining cost (admissible)

Answer

An admissible heuristic never overestimates the true cost to goal, which guarantees that best_plan returns an optimal solution.

Question 3

Which `best_plan` variant also enforces an upper bound on the search cost?

Accepted Answer

best_plan/3 (best_plan(State, Limit, Plan))

Answer

`best_plan/3` takes an explicit Limit argument and returns the cheapest plan whose cost does not exceed that limit.

Question 4

What mechanism does the Picat planner use to avoid re-expanding already-visited states?

Accepted Answer

Tabling (memoization of visited states)

Answer

The planner automatically tables visited states so that the same state is never expanded twice, preventing infinite loops and redundant work.

Question 5

In a `best_plan` search, what happens when two plans have the same total cost?

Accepted Answer

The planner returns whichever it finds first during its search

Answer

The planner returns the first optimal-cost plan it discovers; tie-breaking among equal-cost plans is not specified and depends on search order.

Picat Practice Test