parameters: (alpha)
return_statement: return pyspiel.kuhn_poker.get_optimal_policy(alpha)
docstring: Returns a Nash Equilibrium in Kuhn parameterized by alpha in [0, 1/3].
  
    See https://en.wikipedia.org/wiki/Kuhn_poker#Optimal_strategy
  
    Args:
      alpha: The probability to bet on a Jack for Player 0.
  
    Raises:
      ValueError: If `alpha` is not within [0, 1/3].
docstring_summary: Returns a Nash Equilibrium in Kuhn parameterized by alpha in [0, 1/3].
docstring_tokens: Returns a Nash Equilibrium in Kuhn parameterized by alpha in [ 0 1 / 3 ] .
function: def kuhn_nash_equilibrium(alpha):
    """Returns a Nash Equilibrium in Kuhn parameterized by alpha in [0, 1/3].
  
    See https://en.wikipedia.org/wiki/Kuhn_poker#Optimal_strategy
  
    Args:
      alpha: The probability to bet on a Jack for Player 0.
  
    Raises:
      ValueError: If `alpha` is not within [0, 1/3].
    """
    if not 0 <= alpha <= 1 / 3:
      raise ValueError("alpha ({}) must be in [0, 1/3]".format(alpha))
    return pyspiel.kuhn_poker.get_optimal_policy(alpha)
function_tokens: def kuhn_nash_equilibrium ( alpha ) : if not 0 <= alpha <= 1 / 3 : raise ValueError ( "alpha ({}) must be in [0, 1/3]" . format ( alpha ) ) return pyspiel . kuhn_poker . get_optimal_policy ( alpha )