[15 pts] Consider the Generalized Arc Consistency algorithm from the slides, and Chapte 4 of the Poole & Mackworth book. Determine the worst-case asymptotic running time of this algorithm as a function of the number of variables Vl, the number of constraints ICl, and (if necessary) the size ID of the domains. I recommend you answer on a separate page 1: Procedure GAC(VdomC) 2: Inputs 3: V: a set of varables dom: a function such that domtx) is the domain of variable X C: set of constraints to be satisfied 5: 6: 7: 8: 9: 10 Output arc-consistent domains for each variable Local Dx is a set of values for each variableX TDA is a set of arcs for each variable Xdo 12: Dx -dom(x) while (TDA 0) 15: 16 17 18- 19 20: 21 select o) ETDA NDy (xl x eDx and some pex.Y,-y,, if (NDtDJ then M-wec where y, eRmfor all 0 TDA TDA UR.cyx escope(C), c' is not c. ZEscoe(c') \ p } return (D X is a variable) [15 pts] Consider the Generalized Arc Consistency algorithm from the slides, and Chapte 4 of the Poole & Mackworth book. Determine the worst-case asymptotic running time of this algorithm as a function of the number of variables Vl, the number of constraints ICl, and (if necessary) the size ID of the domains. I recommend you answer on a separate page 1: Procedure GAC(VdomC) 2: Inputs 3: V: a set of varables dom: a function such that domtx) is the domain of variable X C: set of constraints to be satisfied 5: 6: 7: 8: 9: 10 Output arc-consistent domains for each variable Local Dx is a set of values for each variableX TDA is a set of arcs for each variable Xdo 12: Dx -dom(x) while (TDA 0) 15: 16 17 18- 19 20: 21 select o) ETDA NDy (xl x eDx and some pex.Y,-y,, if (NDtDJ then M-wec where y, eRmfor all 0 TDA TDA UR.cyx escope(C), c' is not c. ZEscoe(c') \ p } return (D X is a variable)