class_docstr: Initialise a PomdpXWriter Object
  
  Parameters
  ----------
      model: A Bayesian of Markov Model
          The model to write
  
  encoding: String(optional)
      Encoding for text data
  
  prettyprint: Bool(optional)
      Indentation in output XML if true
class_docstr_tok: ["Initialise","a","PomdpXWriter","Object","Parameters","--","--","--","--","--","model",":","A","Bayesian","of","Markov","Model","The","model","to","write","encoding",":","String","(","optional",")","Encoding","for","text","data","prettyprint",":","Bool","(","optional",")","Indentation","in","output","XML","if","true"]
docstr: add initial belief tag to pomdpx model
  
  Return
  ---------------
  string containing the xml for initial belief tag
docstr_tok: ["add","initial","belief","tag","to","pomdpx","model","Return","--","--","--","--","--","--","--","-","string","containing","the","xml","for","initial","belief","tag"]
code: def add_initial_belief(self):
      """
      add initial belief tag to pomdpx model
  
      Return
      ---------------
      string containing the xml for initial belief tag
      """
      initial_belief = self.model["initial_state_belief"]
      for condition in initial_belief:
          condprob = etree.SubElement(self.initial_belief, "CondProb")
          self.add_conditions(condition, condprob)
      return self.__str__(self.initial_belief)[:-1]
  
imports: import xml.etree.ElementTree
  from collections import defaultdict
label_desc: Use image node_id 8 for calling the PomdpXWriter obj's underlying member method code with example usage: obj.add_initial_belief() and returns: self