What is K consistency?
K-consistency (Path Consistency) A graph is K-consistent if the following is true: Choose values of any K-1 variables that satisfy all the constraints among these variables and choose any Kth variable. Then there exists a value for this Kth variable that satisfies all the constraints among these K variables.
What is local consistency state and explain any three types of local consistency?
Various kinds of local consistency conditions are leveraged, including node consistency, arc consistency, and path consistency. Every local consistency condition can be enforced by a transformation that changes the problem without changing its solutions. Such a transformation is called constraint propagation.
What is adaptive consistency?
Given a network R, adaptive consistency (either version adc1 or adc) determines the consistency of R, and if the network is consistent, it also generates an equivalent representation Ed(R) that is backtrack-free along d.
What is domain consistent?
A variable is domain consistent if no value of the domain of the node is ruled impossible by any of the constraints. Example: dom(B) = {1,2,3,4} isn’t domain consistent if we have the constraint B \= 3.
What is path consistency in CSP?
A CSP is path consistent, if every path is consistent. This definition is long but not difficult to decipher. On top of binary constraints between two variables, path consistency certifies binary consistency between the variables on a path. It is not difficult to see that path consistency implies arc consistency.
Which of the following statements is are true regarding adaptive consistency?
Which of the following statements is/are true regarding Adaptive Consistency? Adaptive Consistency processes variables from first to last in the given order. Adaptive Consistency adapts the ordering to require minimum consistency enforcement.
What is consistency in AI?
Consistent Heuristic in the study of path-finding problems in artificial intelligence, a heuristic function is said to be consistent, or monotone, if its estimate is always less than or equal to the estimated distance from any neighboring vertex to the goal, plus the cost of reaching that neighbor.
Which of the following problems can be modeled as constraint satisfaction problem?
Examples of problems that can be modeled as a constraint satisfaction problem include: Type inference. Eight queens puzzle. Map coloring problem.
Is the Manhattan heuristic consistent?
The heuristic, while less informative than Manhattan distance of all tiles, is still admissible and consistent.
What is consistency in A * algorithm?
In the A* search algorithm, using a consistent heuristic means that once a node is expanded, the cost by which it was reached is the lowest possible, under the same conditions that Dijkstra’s algorithm requires in solving the shortest path problem (no negative cost edges).