Proceedings of the Annual Meeting of the Cognitive Science Society

The ability to selectively attend to stimuli increases the efficiency of learning. However, learning traps can develop when attention prematurely narrows to a subset of the features that predict outcomes, resulting in suboptimal decisions. The current work investigated the potential for learning traps to be particularly damaging in dynamic environments, where the features that predict rewards and losses change during learning. Two experiments (N=316) found that when learners received choice-contingent feedback, they frequently fell into a learning trap, using a suboptimal categorisation rule. Critically, these learners were unlikely to detect a subsequent rule change nor learn the new optimal rule. This change blindness was not attenuated by priming participants to expect change. These results show that the pernicious effects of learning traps are amplified in dynamic environments.