reasoning with constraints cspconsistency py -(continued from cspexamples import test_csp def ac_solver(csp)"arc consistency (solve_one)return con_solver(cspsolve_one( if __name__ ="__main__"test_csp(ac_solverdomain splitting as an interface to graph searching an alternative implementation is to implement domain splitting in terms of the search abstraction of node is domains dictionary cspconsistency py -(continued from searchproblem import arcsearch_problem class search_with_ac_from_csp(search_problem,displayable)""" search problem with arc consistency and domain splitting node is csp ""def __init__(selfcsp)self cons con_solver(csp#copy of the csp self domains self cons make_arc_consistent( def is_goal(selfnode)"""node is goal if all domains have element""return all(len(node[var])== for var in node def start_node(self)return self domains def neighbors(self,node)"""returns the neighboring nodes of node ""neighs [var select( for in node if len(node[ ])> if vardom dom partition_domain(node[var]self display( ,"splitting"var"into"dom "and"dom to_do self cons new_to_do(var,nonefor dom in [dom ,dom ]newdoms copy_with_assign(node,var,domcons_doms self cons make_arc_consistent(newdoms,to_doif all(len(cons_doms[ ])> for in cons_doms)all domains are non-empty neighs append(arc(node,cons_doms)elseversion june