Blocking in human causal learning is affected by outcome assumptions manipulated through causal structure

Additivity-related assumptions have been proven to modulate blocking in human causal learning. Typically, these assumptions are manipulated by means of pretraining phases (including exposure to different outcome magnitudes), or through explicit instructions. In two experiments, we used a different approach that involved neither pretraining nor instructional manipulations. Instead, we manipulated the causal structure in which the cues were embedded, thereby appealing directly to the participants' prior knowledge about causal relations and how causes would add up to yield stronger outcomes. Specifically, in our "different-system" condition, the participants should assume that the outcomes would add up, whereas in our "same-system" condition, a ceiling effect would prevent such an assumption. Consistent with our predictions, Experiment 1 showed that, when two cues from separate causal systems were combined, the participants did expect a stronger outcome on compound trials, and blocking was found, whereas when the cues belonged to the same causal system, the participants did not expect a stronger outcome on compound trials, and blocking was not observed. The results were partially replicated in Experiment 2, in which this pattern was found when the cues were tested for the second time. This evidence supports the claim that prior knowledge about the nature of causal relations can affect human causal learning. In addition, the fact that we did not manipulate causal assumptions through pretraining renders the results hard to account for with associative theories of learning.status: publishe