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AOStar.py
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AOStar.py
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"""Recursive implementation of AO* algorithm"""
class Graph:
def __init__(self, graph, heuristicNodeList, startNode): # instantiate graph object with graph topology,
# heuristic values, start node
self.graph = graph
self.H = heuristicNodeList
self.start = startNode
self.parent = {}
self.status = {}
self.solutionGraph = {}
def applyAOStar(self): # starts a recursive AO* algorithm
self.aoStar(self.start, False)
def getNeighbors(self, v): # gets the Neighbors of a given node
return self.graph.get(v, '')
def getStatus(self, v): # return the status of a given node
return self.status.get(v, 0)
def setStatus(self, v, val): # set the status of a given node
self.status[v] = val
def getHeuristicNodeValue(self, n):
return self.H.get(n, 0) # always return the heuristic value of a given node
def setHeuristicNodeValue(self, n, value):
self.H[n] = value # set the revised heuristic value of a given node
def printSolution(self):
print("FOR GRAPH SOLUTION, TRAVERSE THE GRAPH FROM THE START NODE:", self.start)
print("------------------------------------------------------------")
print(self.solutionGraph)
print("------------------------------------------------------------")
def computeMinimumCostChildNodes(self, v): # Computes the Minimum Cost of child nodes of a given node v
minimumCost = 0
costToChildNodeListDict = {}
costToChildNodeListDict[minimumCost] = []
flag = True
for nodeInfoTupleList in self.getNeighbors(v): # iterate over all the set of child node/s
cost = 0
nodeList = []
for c, weight in nodeInfoTupleList:
cost = cost + self.getHeuristicNodeValue(c) + weight
nodeList.append(c)
if flag == True: # initialize Minimum Cost with the cost of first set of child node/s
minimumCost = cost
costToChildNodeListDict[minimumCost] = nodeList # set the Minimum Cost child node/s
flag = False
else: # checking the Minimum Cost nodes with the current Minimum Cost
if minimumCost > cost:
minimumCost = cost
costToChildNodeListDict[minimumCost] = nodeList # set the Minimum Cost child node/s
return minimumCost, costToChildNodeListDict[minimumCost] # return Minimum Cost and Minimum Cost child node/s
def aoStar(self, v, backTracking): # AO* algorithm for a start node and backTracking status flag
print("HEURISTIC VALUES :", self.H)
print("SOLUTION GRAPH :", self.solutionGraph)
print("PROCESSING NODE :", v)
print("-----------------------------------------------------------------------------------------")
if self.getStatus(v) >= 0: # if status node v >= 0, compute Minimum Cost nodes of v
minimumCost, childNodeList = self.computeMinimumCostChildNodes(v)
self.setHeuristicNodeValue(v, minimumCost)
self.setStatus(v, len(childNodeList))
solved = True # check the Minimum Cost nodes of v are solved
for childNode in childNodeList:
self.parent[childNode] = v
if self.getStatus(childNode) != -1:
solved = solved & False
if solved == True: # if the Minimum Cost nodes of v are solved, set the current node status as solved(-1)
self.setStatus(v, -1)
self.solutionGraph[
v] = childNodeList # update the solution graph with the solved nodes which may be a part of
# solution
if v != self.start: # check the current node is the start node for backtracking the current node value
self.aoStar(self.parent[v],
True) # backtracking the current node value with backtracking status set to true
if not backTracking: # check the current call is not for backtracking
for childNode in childNodeList: # for each Minimum Cost child node
self.setStatus(childNode, 0) # set the status of child node to 0(needs exploration)
self.aoStar(childNode,
False) # Minimum Cost child node is further explored with backtracking status as false
h1 = {'A': 1, 'B': 6, 'C': 2, 'D': 12, 'E': 2, 'F': 1, 'G': 5, 'H': 7, 'I': 7, 'J': 1, 'T': 3}
graph1 = {
'A': [[('B', 1), ('C', 1)], [('D', 1)]],
'B': [[('G', 1)], [('H', 1)]],
'C': [[('J', 1)]],
'D': [[('E', 1), ('F', 1)]],
'G': [[('I', 1)]]
}
G1 = Graph(graph1, h1, 'A')
G1.applyAOStar()
G1.printSolution()
h2 = {'A': 1, 'B': 6, 'C': 12, 'D': 10, 'E': 4, 'F': 4, 'G': 5, 'H': 7} # Heuristic values of Nodes
graph2 = { # Graph of Nodes and Edges
'A': [[('B', 1), ('C', 1)], [('D', 1)]], # Neighbors of Node 'A', B, C & D with respective weights
'B': [[('G', 1)], [('H', 1)]], # Neighbors are included in a list of lists
'D': [[('E', 1), ('F', 1)]] # Each sublist indicate a "OR" node or "AND" nodes
}
G2 = Graph(graph2, h2, 'A') # Instantiate Graph object with graph, heuristic values and start Node
G2.applyAOStar() # Run the AO* algorithm
G2.printSolution() # Print the solution graph as output of the AO* algorithm search
########################################################################################################################
# OUTPUT:
# Ignore single quotes at beginning and end
########################################################################################################################
'''
HEURISTIC VALUES : {'A': 1, 'B': 6, 'C': 2, 'D': 12, 'E': 2, 'F': 1, 'G': 5, 'H': 7, 'I': 7, 'J': 1, 'T': 3}
SOLUTION GRAPH : {}
PROCESSING NODE : A
-----------------------------------------------------------------------------------------
HEURISTIC VALUES : {'A': 10, 'B': 6, 'C': 2, 'D': 12, 'E': 2, 'F': 1, 'G': 5, 'H': 7, 'I': 7, 'J': 1, 'T': 3}
SOLUTION GRAPH : {}
PROCESSING NODE : B
-----------------------------------------------------------------------------------------
HEURISTIC VALUES : {'A': 10, 'B': 6, 'C': 2, 'D': 12, 'E': 2, 'F': 1, 'G': 5, 'H': 7, 'I': 7, 'J': 1, 'T': 3}
SOLUTION GRAPH : {}
PROCESSING NODE : A
-----------------------------------------------------------------------------------------
HEURISTIC VALUES : {'A': 10, 'B': 6, 'C': 2, 'D': 12, 'E': 2, 'F': 1, 'G': 5, 'H': 7, 'I': 7, 'J': 1, 'T': 3}
SOLUTION GRAPH : {}
PROCESSING NODE : G
-----------------------------------------------------------------------------------------
HEURISTIC VALUES : {'A': 10, 'B': 6, 'C': 2, 'D': 12, 'E': 2, 'F': 1, 'G': 8, 'H': 7, 'I': 7, 'J': 1, 'T': 3}
SOLUTION GRAPH : {}
PROCESSING NODE : B
-----------------------------------------------------------------------------------------
HEURISTIC VALUES : {'A': 10, 'B': 8, 'C': 2, 'D': 12, 'E': 2, 'F': 1, 'G': 8, 'H': 7, 'I': 7, 'J': 1, 'T': 3}
SOLUTION GRAPH : {}
PROCESSING NODE : A
-----------------------------------------------------------------------------------------
HEURISTIC VALUES : {'A': 12, 'B': 8, 'C': 2, 'D': 12, 'E': 2, 'F': 1, 'G': 8, 'H': 7, 'I': 7, 'J': 1, 'T': 3}
SOLUTION GRAPH : {}
PROCESSING NODE : I
-----------------------------------------------------------------------------------------
HEURISTIC VALUES : {'A': 12, 'B': 8, 'C': 2, 'D': 12, 'E': 2, 'F': 1, 'G': 8, 'H': 7, 'I': 0, 'J': 1, 'T': 3}
SOLUTION GRAPH : {'I': []}
PROCESSING NODE : G
-----------------------------------------------------------------------------------------
HEURISTIC VALUES : {'A': 12, 'B': 8, 'C': 2, 'D': 12, 'E': 2, 'F': 1, 'G': 1, 'H': 7, 'I': 0, 'J': 1, 'T': 3}
SOLUTION GRAPH : {'I': [], 'G': ['I']}
PROCESSING NODE : B
-----------------------------------------------------------------------------------------
HEURISTIC VALUES : {'A': 12, 'B': 2, 'C': 2, 'D': 12, 'E': 2, 'F': 1, 'G': 1, 'H': 7, 'I': 0, 'J': 1, 'T': 3}
SOLUTION GRAPH : {'I': [], 'G': ['I'], 'B': ['G']}
PROCESSING NODE : A
-----------------------------------------------------------------------------------------
HEURISTIC VALUES : {'A': 6, 'B': 2, 'C': 2, 'D': 12, 'E': 2, 'F': 1, 'G': 1, 'H': 7, 'I': 0, 'J': 1, 'T': 3}
SOLUTION GRAPH : {'I': [], 'G': ['I'], 'B': ['G']}
PROCESSING NODE : C
-----------------------------------------------------------------------------------------
HEURISTIC VALUES : {'A': 6, 'B': 2, 'C': 2, 'D': 12, 'E': 2, 'F': 1, 'G': 1, 'H': 7, 'I': 0, 'J': 1, 'T': 3}
SOLUTION GRAPH : {'I': [], 'G': ['I'], 'B': ['G']}
PROCESSING NODE : A
-----------------------------------------------------------------------------------------
HEURISTIC VALUES : {'A': 6, 'B': 2, 'C': 2, 'D': 12, 'E': 2, 'F': 1, 'G': 1, 'H': 7, 'I': 0, 'J': 1, 'T': 3}
SOLUTION GRAPH : {'I': [], 'G': ['I'], 'B': ['G']}
PROCESSING NODE : J
-----------------------------------------------------------------------------------------
HEURISTIC VALUES : {'A': 6, 'B': 2, 'C': 2, 'D': 12, 'E': 2, 'F': 1, 'G': 1, 'H': 7, 'I': 0, 'J': 0, 'T': 3}
SOLUTION GRAPH : {'I': [], 'G': ['I'], 'B': ['G'], 'J': []}
PROCESSING NODE : C
-----------------------------------------------------------------------------------------
HEURISTIC VALUES : {'A': 6, 'B': 2, 'C': 1, 'D': 12, 'E': 2, 'F': 1, 'G': 1, 'H': 7, 'I': 0, 'J': 0, 'T': 3}
SOLUTION GRAPH : {'I': [], 'G': ['I'], 'B': ['G'], 'J': [], 'C': ['J']}
PROCESSING NODE : A
-----------------------------------------------------------------------------------------
FOR GRAPH SOLUTION, TRAVERSE THE GRAPH FROM THE START NODE: A
------------------------------------------------------------
{'I': [], 'G': ['I'], 'B': ['G'], 'J': [], 'C': ['J'], 'A': ['B', 'C']}
------------------------------------------------------------
HEURISTIC VALUES : {'A': 1, 'B': 6, 'C': 12, 'D': 10, 'E': 4, 'F': 4, 'G': 5, 'H': 7}
SOLUTION GRAPH : {}
PROCESSING NODE : A
-----------------------------------------------------------------------------------------
HEURISTIC VALUES : {'A': 11, 'B': 6, 'C': 12, 'D': 10, 'E': 4, 'F': 4, 'G': 5, 'H': 7}
SOLUTION GRAPH : {}
PROCESSING NODE : D
-----------------------------------------------------------------------------------------
HEURISTIC VALUES : {'A': 11, 'B': 6, 'C': 12, 'D': 10, 'E': 4, 'F': 4, 'G': 5, 'H': 7}
SOLUTION GRAPH : {}
PROCESSING NODE : A
-----------------------------------------------------------------------------------------
HEURISTIC VALUES : {'A': 11, 'B': 6, 'C': 12, 'D': 10, 'E': 4, 'F': 4, 'G': 5, 'H': 7}
SOLUTION GRAPH : {}
PROCESSING NODE : E
-----------------------------------------------------------------------------------------
HEURISTIC VALUES : {'A': 11, 'B': 6, 'C': 12, 'D': 10, 'E': 0, 'F': 4, 'G': 5, 'H': 7}
SOLUTION GRAPH : {'E': []}
PROCESSING NODE : D
-----------------------------------------------------------------------------------------
HEURISTIC VALUES : {'A': 11, 'B': 6, 'C': 12, 'D': 6, 'E': 0, 'F': 4, 'G': 5, 'H': 7}
SOLUTION GRAPH : {'E': []}
PROCESSING NODE : A
-----------------------------------------------------------------------------------------
HEURISTIC VALUES : {'A': 7, 'B': 6, 'C': 12, 'D': 6, 'E': 0, 'F': 4, 'G': 5, 'H': 7}
SOLUTION GRAPH : {'E': []}
PROCESSING NODE : F
-----------------------------------------------------------------------------------------
HEURISTIC VALUES : {'A': 7, 'B': 6, 'C': 12, 'D': 6, 'E': 0, 'F': 0, 'G': 5, 'H': 7}
SOLUTION GRAPH : {'E': [], 'F': []}
PROCESSING NODE : D
-----------------------------------------------------------------------------------------
HEURISTIC VALUES : {'A': 7, 'B': 6, 'C': 12, 'D': 2, 'E': 0, 'F': 0, 'G': 5, 'H': 7}
SOLUTION GRAPH : {'E': [], 'F': [], 'D': ['E', 'F']}
PROCESSING NODE : A
-----------------------------------------------------------------------------------------
FOR GRAPH SOLUTION, TRAVERSE THE GRAPH FROM THE START NODE: A
------------------------------------------------------------
{'E': [], 'F': [], 'D': ['E', 'F'], 'A': ['D']}
------------------------------------------------------------
'''