Open-Ended Learning Leads to Generally Capable Agents | AI2

Embodied AI Lecture Series @ PRIOR For previous recordings and upcoming talks visit Open-Ended Learning Leads to Generally Capable Agents Max Jaderberg • DeepMind • (10/1/21) Abstract: In this talk I will cover our recent publication “Open-Ended Learning Leads to Generally Capable Agents“ (). In this work we turn our attention to how to create embodied agents in simulation that can generalise to unseen test tasks and exhibit generally capable behaviour. I will introduce our XLand procedurally generated environment, and the open-ended learning algorithms that allow us to train agents to cover this vast environment space. This results in agents that are capable across a wide range of held-out test tasks including hide-and-seek and capture-the-flag, and we will explore these results and the emergent behaviours and representations of the agent.