Model-based RL uses predictions of the specific consequences of action (i.e., the states that actions lead to) to compute their values. Therefore if ACC implements model-based computations, we expect to see predictions of future state given chosen action and surprise signals if these predictions are violated, both of which require knowledge of the current configuration of the transition probabilities linking first-step actions to second-step states.
