No learning where to go without first knowing where you're coming from: action discovery is trajectory, not endpoint based

Intrinsic motivations drive an agent to explore, providing essential data for linking behaviors with novel outcomes and so laying the foundation for future flexible action. We present experiments using a new behavioral task which allows us to interrogate the connection between exploration and action learning. Human participants used a joystick to search repeatedly for a target location, only receiving feedback on successful discovery. Feedback delay was manipulated, as was the starting position. Experiment 1 employed stable starting positions, so the task could be learnt with respect to a target location or a target trajectory. Participants were able to learn the correct movement under all delay conditions. Experiment 2 used a variable starting location, so the correct movement could only be learnt in terms of target location. Participants displayed little to no learning in this experiment. These results suggest that movements on this scale are stored as trajectories rather than in terms of target location. Overall the experiments demonstrate the potential of this task for uncovering the native representational substrates of action learning.