Accounting for sensitivity of latent learning to behavioral statistics with successor representations
Fig 7
Experimental task design influences latent learning.
Comparison of latent learning agents with three pre-exposure designs (targeted, continuous, mistargeted) to the direct learning agent for the gridworld. Lines indicate averages across 30 simulations and shaded regions the S.E.M. A) Performance in the grid world for agents using deep SR based on one-hot encodings (first row), deep SR based on image-representations (second row), and image-based Dyna-DQN (third row). B) Same as in A) for the Tolman maze.