Attention Guided Imitation Learning and Reinforcement Learning

No. 1: AAAI-19, IAAI-19, EAAI-20

Volume

Proceedings of the AAAI Conference on Artificial Intelligence, 33

Doctoral Consortium Track

We propose a framework that uses learned human visual attention model to guide the learning process of an imitation learning or reinforcement learning agent. We have collected high-quality human action and eye-tracking data while playing Atari games in a carefully controlled experimental setting. We have shown that incorporating a learned human gaze model into deep imitation learning yields promising results.

10.1609/aaai.v33i01.33019906