Keras models break when I add batch normalization
This link describes the cause of the problem. Its because we try to feed a placeholder defined as an Input layer using another input layer. You can modify your code as follows:

def buildDDPGNets(actNum, obsSpace):

  actorObsInput = Input(shape = (1,) + obsSpace, name = "actor_obs_input")
  criticActInput = Input(shape = (actNum,), name = "critic_action_input")

  flattened_obs = Flatten()(actorObsInput)
  a = Dense(600, use_bias = False)(flattened_obs)
  a = BatchNormalization()(a)
  a = Activation("relu")(a)
  a = Dense(300, use_bias = False)(a)
  a = BatchNormalization()(a)
  a = Activation("relu")(a)
  a = Dense(actNum)(a)
  a = Activation("tanh")(a)   # Bipdeal walker applies torque (-1, 1).
  actor = Model(inputs = [actorObsInput], outputs = a)

  c = Dense(600, use_bias = False)(flattened_obs)
  c = BatchNormalization()(c)
  c = Activation("relu")(c)
  c = Concatenate()([c, criticActInput])
  c = Dense(300, use_bias = False)(c)
  c = BatchNormalization()(c)
  c = Activation("relu")(c)
  c = Dense(1)(c)
  c = Activation("linear")(c)
  critic = Model(inputs = [criticActInput, criticObsInput], outputs = c)

  return (criticActInput, actor, critic)