parameters: (state, fitness)
return_statement: return state * (fitness - avg_fitness)
docstring: Continuous-time replicator dynamics.
  
    This is the standard form of the continuous-time replicator dynamics also
    known as selection dynamics.
  
    For more details, see equation (5) page 9 in
    https://jair.org/index.php/jair/article/view/10952
  
    Args:
      state: Probability distribution as an `np.array(shape=num_strategies)`.
      fitness: Fitness vector as an `np.array(shape=num_strategies)`.
  
    Returns:
      Time derivative of the population state.
docstring_summary: Continuous-time replicator dynamics.
docstring_tokens: Continuous - time replicator dynamics .
function: def replicator(state, fitness):
    """Continuous-time replicator dynamics.
  
    This is the standard form of the continuous-time replicator dynamics also
    known as selection dynamics.
  
    For more details, see equation (5) page 9 in
    https://jair.org/index.php/jair/article/view/10952
  
    Args:
      state: Probability distribution as an `np.array(shape=num_strategies)`.
      fitness: Fitness vector as an `np.array(shape=num_strategies)`.
  
    Returns:
      Time derivative of the population state.
    """
    avg_fitness = state.dot(fitness)
    return state * (fitness - avg_fitness)
function_tokens: def replicator ( state , fitness ) : avg_fitness = state . dot ( fitness ) return state * ( fitness - avg_fitness )