Lazy-MDPs: Towards Interpretable Reinforcement Learning by Learning When to Act

Alexis Jacq, Johan Ferret, Olivier Pietquin +1

Traditionally, Reinforcement Learning (RL) aims at deciding how to act optimally for an artificial agent. We argue that deciding when to act is equally important. As humans, we dri…