Accounting for sensitivity of latent learning to behavioral statistics with successor representations
Fig 10
Targeted pre-exposure drives more optimal action selection than continuous pre-exposure in Tolman maze.
Left and middle: Thin lines represent the optimality trace of a single simulation. For each trial, optimality was quantified as the ratio of optimal actions to the total number of actions taken across all states that transition to the goal, i.e., excluding dead-end states. Thick lines represent the average over 30 simulations. Right: The agents’ optimality ratios show that targeted pre-exposure consistently outperforms continuous pre-exposure in all trials. Average over 30 simulations, shaded regions indicate S.E.M.