# searchProblem.py - representations of search problems # AIFCA Python3 code Version 0.9.5 Documentation at http://aipython.org # Download the zip file and read aipython.pdf for documentation # Artificial Intelligence: Foundations of Computational Agents http://artint.info # Copyright David L Poole and Alan K Mackworth 2017-2022. # This work is licensed under a Creative Commons # Attribution-NonCommercial-ShareAlike 4.0 International License. # See: http://creativecommons.org/licenses/by-nc-sa/4.0/deed.en class Search_problem(object): """A search problem consists of: * a start node * a neighbors function that gives the neighbors of a node * a specification of a goal * a (optional) heuristic function. The methods must be overridden to define a search problem.""" def start_node(self): """returns start node""" raise NotImplementedError("start_node") # abstract method def is_goal(self,node): """is True if node is a goal""" raise NotImplementedError("is_goal") # abstract method def neighbors(self,node): """returns a list of the arcs for the neighbors of node""" raise NotImplementedError("neighbors") # abstract method def heuristic(self,n): """Gives the heuristic value of node n. Returns 0 if not overridden.""" return 0 class Arc(object): """An arc has a from_node and a to_node node and a (non-negative) cost""" def __init__(self, from_node, to_node, cost=1, action=None): assert cost >= 0, ("Cost cannot be negative for"+ str(from_node)+"->"+str(to_node)+", cost: "+str(cost)) self.from_node = from_node self.to_node = to_node self.action = action self.cost=cost def __repr__(self): """string representation of an arc""" if self.action: return str(self.from_node)+" --"+str(self.action)+"--> "+str(self.to_node) else: return str(self.from_node)+" --> "+str(self.to_node) class Search_problem_from_explicit_graph(Search_problem): """A search problem consists of: * a list or set of nodes * a list or set of arcs * a start node * a list or set of goal nodes * a dictionary that maps each node into its heuristic value. * a dictionary that maps each node into its (x,y) position """ def __init__(self, nodes, arcs, start=None, goals=set(), hmap={}, positions={}): self.neighs = {} self.nodes = nodes for node in nodes: self.neighs[node]=[] self.arcs = arcs for arc in arcs: self.neighs[arc.from_node].append(arc) self.start = start self.goals = goals self.hmap = hmap self.positions = positions def start_node(self): """returns start node""" return self.start def is_goal(self,node): """is True if node is a goal""" return node in self.goals def neighbors(self,node): """returns the neighbors of node""" return self.neighs[node] def heuristic(self,node): """Gives the heuristic value of node n. Returns 0 if not overridden in the hmap.""" if node in self.hmap: return self.hmap[node] else: return 0 def __repr__(self): """returns a string representation of the search problem""" res="" for arc in self.arcs: res += str(arc)+". " return res def neighbor_nodes(self,node): """returns an iterator over the neighbors of node""" return (path.to_node for path in self.neighs[node]) class Path(object): """A path is either a node or a path followed by an arc""" def __init__(self,initial,arc=None): """initial is either a node (in which case arc is None) or a path (in which case arc is an object of type Arc)""" self.initial = initial self.arc=arc if arc is None: self.cost=0 else: self.cost = initial.cost+arc.cost def end(self): """returns the node at the end of the path""" if self.arc is None: return self.initial else: return self.arc.to_node def nodes(self): """enumerates the nodes for the path. This starts at the end and enumerates nodes in the path backwards.""" current = self while current.arc is not None: yield current.arc.to_node current = current.initial yield current.initial def initial_nodes(self): """enumerates the nodes for the path before the end node. This starts at the end and enumerates nodes in the path backwards.""" if self.arc is not None: yield from self.initial.nodes() def __repr__(self): """returns a string representation of a path""" if self.arc is None: return str(self.initial) elif self.arc.action: return (str(self.initial)+"\n --"+str(self.arc.action) +"--> "+str(self.arc.to_node)) else: return str(self.initial)+" --> "+str(self.arc.to_node) problem1 = Search_problem_from_explicit_graph( {'A','B','C','D','G'}, [Arc('A','B',3), Arc('A','C',1), Arc('B','D',1), Arc('B','G',3), Arc('C','B',1), Arc('C','D',3), Arc('D','G',1)], start = 'A', goals = {'G'}, positions={'A': (0, 2), 'B': (1, 1), 'C': (0,1), 'D': (1,0), 'G': (2,0)}) problem2 = Search_problem_from_explicit_graph( {'a','b','c','d','e','g','h','j'}, [Arc('a','b',1), Arc('b','c',3), Arc('b','d',1), Arc('d','e',3), Arc('d','g',1), Arc('a','h',3), Arc('h','j',1)], start = 'a', goals = {'g'}, positions={'a': (0, 0), 'b': (0, 1), 'c': (0,4), 'd': (1,1), 'e': (1,4), 'g': (2,1), 'h': (3,0), 'j': (3,1)}) problem3 = Search_problem_from_explicit_graph( {'a','b','c','d','e','g','h','j'}, [], start = 'g', goals = {'k','g'}) simp_delivery_graph = Search_problem_from_explicit_graph( {'A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'J'}, [ Arc('A', 'B', 2), Arc('A', 'C', 3), Arc('A', 'D', 4), Arc('B', 'E', 2), Arc('B', 'F', 3), Arc('C', 'J', 7), Arc('D', 'H', 4), Arc('F', 'D', 2), Arc('H', 'G', 3), Arc('J', 'G', 4)], start = 'A', goals = {'G'}, hmap = { 'A': 7, 'B': 5, 'C': 9, 'D': 6, 'E': 3, 'F': 5, 'G': 0, 'H': 3, 'J': 4, }) cyclic_simp_delivery_graph = Search_problem_from_explicit_graph( {'A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'J'}, [ Arc('A', 'B', 2), Arc('A', 'C', 3), Arc('A', 'D', 4), Arc('B', 'A', 2), Arc('B', 'E', 2), Arc('B', 'F', 3), Arc('C', 'A', 3), Arc('C', 'J', 7), Arc('D', 'A', 4), Arc('D', 'H', 4), Arc('F', 'B', 3), Arc('F', 'D', 2), Arc('G', 'H', 3), Arc('G', 'J', 4), Arc('H', 'D', 4), Arc('H', 'G', 3), Arc('J', 'C', 6), Arc('J', 'G', 4)], start = 'A', goals = {'G'}, hmap = { 'A': 7, 'B': 5, 'C': 9, 'D': 6, 'E': 3, 'F': 5, 'G': 0, 'H': 3, 'J': 4, }) acyclic_delivery_problem = Search_problem_from_explicit_graph( {'mail','ts','o103','o109','o111','b1','b2','b3','b4','c1','c2','c3', 'o125','o123','o119','r123','storage'}, [Arc('ts','mail',6), Arc('o103','ts',8), Arc('o103','b3',4), Arc('o103','o109',12), Arc('o109','o119',16), Arc('o109','o111',4), Arc('b1','c2',3), Arc('b1','b2',6), Arc('b2','b4',3), Arc('b3','b1',4), Arc('b3','b4',7), Arc('b4','o109',7), Arc('c1','c3',8), Arc('c2','c3',6), Arc('c2','c1',4), Arc('o123','o125',4), Arc('o123','r123',4), Arc('o119','o123',9), Arc('o119','storage',7)], start = 'o103', goals = {'r123'}, hmap = { 'mail' : 26, 'ts' : 23, 'o103' : 21, 'o109' : 24, 'o111' : 27, 'o119' : 11, 'o123' : 4, 'o125' : 6, 'r123' : 0, 'b1' : 13, 'b2' : 15, 'b3' : 17, 'b4' : 18, 'c1' : 6, 'c2' : 10, 'c3' : 12, 'storage' : 12 } ) cyclic_delivery_problem = Search_problem_from_explicit_graph( {'mail','ts','o103','o109','o111','b1','b2','b3','b4','c1','c2','c3', 'o125','o123','o119','r123','storage'}, [ Arc('ts','mail',6), Arc('mail','ts',6), Arc('o103','ts',8), Arc('ts','o103',8), Arc('o103','b3',4), Arc('o103','o109',12), Arc('o109','o103',12), Arc('o109','o119',16), Arc('o119','o109',16), Arc('o109','o111',4), Arc('o111','o109',4), Arc('b1','c2',3), Arc('b1','b2',6), Arc('b2','b1',6), Arc('b2','b4',3), Arc('b4','b2',3), Arc('b3','b1',4), Arc('b1','b3',4), Arc('b3','b4',7), Arc('b4','b3',7), Arc('b4','o109',7), Arc('c1','c3',8), Arc('c3','c1',8), Arc('c2','c3',6), Arc('c3','c2',6), Arc('c2','c1',4), Arc('c1','c2',4), Arc('o123','o125',4), Arc('o125','o123',4), Arc('o123','r123',4), Arc('r123','o123',4), Arc('o119','o123',9), Arc('o123','o119',9), Arc('o119','storage',7), Arc('storage','o119',7)], start = 'o103', goals = {'r123'}, hmap = { 'mail' : 26, 'ts' : 23, 'o103' : 21, 'o109' : 24, 'o111' : 27, 'o119' : 11, 'o123' : 4, 'o125' : 6, 'r123' : 0, 'b1' : 13, 'b2' : 15, 'b3' : 17, 'b4' : 18, 'c1' : 6, 'c2' : 10, 'c3' : 12, 'storage' : 12 } )