APPLE is an RL framework that jointly optimizes a transformer perception module and policy via a unified objective for general active perception, with evaluations on tactile MNIST regression and classification tasks.
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Apple: Toward General Active Perception via Reinforcement Learning
APPLE is an RL framework that jointly optimizes a transformer perception module and policy via a unified objective for general active perception, with evaluations on tactile MNIST regression and classification tasks.