Curiosity-Driven Learning – Exploration By Random Network Distillation

In recent years, Reinforcement Learning has proven itself to be a powerful technique for solving closed tasks with constant rewards, most commonly games. A major challenge in the field remains training a model when external feedback (reward) to actions is sparse or nonexistent. Recent models have tried to overcome this challenge by creating an intrinsic […]