Learning Representations in Video Game Agents with Supervised Contrastive Imitation Learning

Carlos Celemin, Joseph Brennan, Pierluigi Vito Amadori +1

This paper introduces a novel application of Supervised Contrastive Learning (SupCon) to Imitation Learning (IL), with a focus on learning more effective state representations for…