Generalizing to generalize: Humans flexibly switch between compositional and conjunctive structures during reinforcement learning

Nicholas T. Franklin, Michael J. Frank

Abstract: Author summary To act in new situations, people not only have to generalize from previous experiences, but they also have to decide how to do so. One strategy is to re-use behaviors they’ve already learned, but this will only be helpful if all aspects of the new situation are similar enough. Alternatively, people can combine knowledge from multiple sources and devise a new plan. For example, a skilled musician may re-use the hand motions learned playing the guitar to play a different style of music on a banjo. Previous theoretical work has suggested that the best strategy is to learn from the statistics of the environment to decide how to best generalize, whereby some environments imply that all parts of a task should be re-used as a whole, whereas others suggest that different components can be generalized separately. Here, we test whether people’s generalization strategy changes with their environment using three navigation tasks, in which people have to decide both where they want to go and how to get there. We varied whether it was advantageous to generalize these two pieces of information separately or together and found that people adapted their generalization in line with an optimal computational model of meta generalization. These results suggest that people not only generalize what they learn within a single task, but they also generalize their generalization strategy as well.