parameters: (self, node)
return_statement: return node.backwards_cost + self.heuristic_fn(node.state)
docstring: Calculates the estimated total cost of going from node to goal
          
          Args:
              node (SearchNode): node of the state we are interested in
          
          Returns:
              float: h(s) + g(s), where g is the total backwards cost
docstring_summary: Calculates the estimated total cost of going from node to goal
          
          Args:
              node (SearchNode): node of the state we are interested in
          
          Returns:
              float: h(s) + g(s), where g is the total backwards cost
docstring_tokens: Calculates the estimated total cost of going from node to goal Args : node ( SearchNode ) : node of the state we are interested in Returns : float : h ( s ) + g ( s ) where g is the total backwards cost
function: def estimated_total_cost(self, node):
          """
          Calculates the estimated total cost of going from node to goal
          
          Args:
              node (SearchNode): node of the state we are interested in
          
          Returns:
              float: h(s) + g(s), where g is the total backwards cost
          """
          return node.backwards_cost + self.heuristic_fn(node.state)
function_tokens: def estimated_total_cost ( self , node ) : return node . backwards_cost + self . heuristic_fn ( node . state )