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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def get_initial_beliefs(self):
 """ Returns the state, action and observation variables as a dictionary in the case of table type parameter and a nested structure in case of decision diagram parameter Examples -------- [{'Var': 'rover_0', 'Parent': ['null'], 'Type': 'TBL', 'Parameter': [{'Instance': ['-'], 'ProbTable': ['0.0', '1.0', '0.0']}] }, {'Var': '', }] """

        initial_state_belief = []
        for variable in self.network.findall('InitialStateBelief'):
            for var in variable.findall('CondProb'):
                cond_prob = defaultdict(list)
                cond_prob['Var'] = var.find('Var').text
                cond_prob['Parent'] = var.find('Parent').text.split()
                if not var.find('Parameter').get('type'):
                    cond_prob['Type'] = 'TBL'
                else:
                    cond_prob['Type'] = var.find('Parameter').get('type')
                cond_prob['Parameter'] = self.get_parameter(var)
                initial_state_belief.append(cond_prob)

        return initial_state_belief