That Escalated Quickly: Compounding Complexity by Editing Levels at the Frontier of Agent Capabilities

no code implementations • 29 Sep 2021 • Jack Parker-Holder, Minqi Jiang, Michael D Dennis, Mikayel Samvelyan, Jakob Nicolaus Foerster, Edward Grefenstette, Tim Rocktäschel

Deep Reinforcement Learning (RL) has recently produced impressive results in a series of settings such as games and robotics.

Reinforcement Learning (RL)

Benefits of Assistance over Reward Learning

no code implementations • 1 Jan 2021 • Rohin Shah, Pedro Freire, Neel Alex, Rachel Freedman, Dmitrii Krasheninnikov, Lawrence Chan, Michael D Dennis, Pieter Abbeel, Anca Dragan, Stuart Russell

By merging reward learning and control, assistive agents can reason about the impact of control actions on reward learning, leading to several advantages over agents based on reward learning.