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Found 5 papers, 1 papers with code
Unveiling the Significance of Toddler-Inspired Reward Transition in Goal-Oriented Reinforcement Learning
Toddlers evolve from free exploration with sparse feedback to exploiting prior experiences for goal-directed learning with denser rewards.
Visual Hindsight Self-Imitation Learning for Interactive Navigation
Interactive visual navigation tasks, which involve following instructions to reach and interact with specific targets, are challenging not only because successful experiences are very rare but also because the complex visual inputs require a substantial number of samples.
L-SA: Learning Under-Explored Targets in Multi-Target Reinforcement Learning
Tasks that involve interaction with various targets are called multi-target tasks.
Learning Geometry-aware Representations by Sketching
Our method, coined Learning by Sketching (LBS), learns to convert an image into a set of colored strokes that explicitly incorporate the geometric information of the scene in a single inference step without requiring a sketch dataset.
Goal-Aware Cross-Entropy for Multi-Target Reinforcement Learning
Learning in a multi-target environment without prior knowledge about the targets requires a large amount of samples and makes generalization difficult.
