Generalizing Emergent Communication

Understand

We converted the recently developed BabyAI grid world platform to a sender/receiver setup in order to test the hypothesis that established deep reinforcement learning techniques are sufficient to incentivize the emergence of a grounded discrete communication protocol between generalized agents.

• This is in contrast to previous experiments that employed straight-through estimation or specialized inductive biases.
• Our results show that these can indeed be avoided, by instead providing proper environmental incentives.
• Moreover, they show that a longer interval between communications incentivized more abstract semantics.