Switching Attention Learning – a Paradigm for Introspection and Incremental Learning

Humans improve their sport skills by eliminating one recognizable weakness at a time. Inspired by this observation, we define a learning paradigm in which different learners can be plugged together. An extra attention model is in charge of iterating over them and chosing which one to improve next. The paradigm is named Switching Attention Learning (SAL). The essential idea is that improving one model in the system generates more “improvement space” for the others. Using SAL, an application for tracking the game ball in a table soccer game-recorder is implemented. We developed several models and learners which work together in the SAL framework, producing satisfying results in the experiments. The related problems, advantages, and perspective of the switching attention learning are discussed in this paper.