class_docstr: An Agent class for all optimization techniques.
class_docstr_tok: ["An","Agent","class","for","all","optimization","techniques","."]
docstr: Fills the agent's decision variables with a binary distribution.
docstr_tok: ["Fills","the","agent","'s","decision","variables","with","a","binary","distribution","."]
code: def fill_with_binary(self) -> None:
      """Fills the agent's decision variables with a binary distribution."""
  
      for j in range(self.n_variables):
          self.position[j] = r.generate_binary_random_number(
              self.n_dimensions
          )
  
imports: import time
  from typing import Dict, List, Optional, Union
  import numpy
  import opytimizer.math.random
  import opytimizer.utils.constant
  import opytimizer.utils.exception
  from opytimizer.utils import logging
label_desc: Use image node_id 20 for calling the Agent obj's underlying member method code with example usage: obj.fill_with_binary() without return types