Topic: compositional learning

In a recent experiment, Shamash et al. demonstrated that mice spontaneously adopt a subgoal strategy when escaping to a shelter hidden behind a wall. Their optimized trajectory, learned in 1-3 trials, involves running straight to a subgoal located at the edge of the wall, and then to the shelter. Strikingly, even if the wall is removed, animals consistently show curved escape trajectories, revealing that they continue to use the subgoal even though this involves a detour. This behavior can disappear depending on the details of the environment configuration during initial exploration, and can s

Fast and adaptable learning is often characterized by sudden jumps in performance rather than slow adaptation typical of updating synaptic weights. Cognitive science theories posit that rapid insights are due to compositional symbolic representations that allow animals to quickly recombine past knowledge to adapt to new settings. Traditionally, it has been difficult to model this type of compositional learning with neural systems. Here we leverage recent work on compositional computations in multitasking Recurrent Neural Networks (RNNs) to construct a neural model of compositional learning. Pa