class_docstr: An online Q-lambda agent.
class_docstr_tok: ["An","online","Q-lambda","agent","."]
code: def __init__(
      self,
      observation_spec,
      action_spec,
      num_hidden_units,
      epsilon,
      lambda_,
      learning_rate,
  ):
      self._observation_spec = observation_spec
      self._action_spec = action_spec
      self._epsilon = epsilon
      self._lambda = lambda_
  
      # Neural net and optimiser.
      self._network = build_network(
          num_hidden_units, action_spec.num_values
      )
  
      self._optimizer = optax.adam(learning_rate)
      # Jitting for speed.
      self.actor_step = jax.jit(self.actor_step)
      self.learner_step = jax.jit(self.learner_step)
  
imports: import collections
  from absl import app
  from absl import flags
  from bsuite.environments import catch
  import dm_env
  import haiku
  from haiku import nets
  import jax
  import jax.numpy
  import numpy
  import optax
  import rlax
  from rlax.examples import experiment
label_desc: Use image node_id 1 to create a new OnlineQLambda object  with example: obj = OnlineQLambda(observation_spec, action_spec, num_hidden_units, epsilon, lambda_, learning_rate)