activity
20172022
most citedEmergence of Locomotion Behaviours in Rich Environments

668 citations · 875 across the 13 of their papers we have counts for

collaborators
Showing 2018Show all

8 papers · 1 filter

cs.LG2018

Learning Attractor Dynamics for Generative Memory

Yan Wu, Greg Wayne, Karol Gregor +1

A central challenge faced by memory systems is the robust retrieval of a stored pattern in the presence of interference due to other stored patterns and noise. A theoretically well…

cs.LG2018

Neural probabilistic motor primitives for humanoid control

Josh Merel, Leonard Hasenclever, Alexandre Galashov +5

We focus on the problem of learning a single motor module that can flexibly express a range of behaviors for the control of high-dimensional physically simulated humanoids. To do t…

cs.LG2018

Experience Replay for Continual Learning

David Rolnick, Arun Ahuja, Jonathan Schwarz +2

Continual learning is the problem of learning new tasks or knowledge while protecting old knowledge and ideally generalizing from old experience to learn new tasks faster. Neural n…

cs.AI2018

Hierarchical visuomotor control of humanoids

Josh Merel, Arun Ahuja, Vu Pham +5

We aim to build complex humanoid agents that integrate perception, motor control, and memory. In this work, we partly factor this problem into low-level motor control from proprioc…

cs.AI2018

Optimizing Agent Behavior over Long Time Scales by Transporting Value

Chia-Chun Hung, Timothy Lillicrap, Josh Abramson +5

Humans spend a remarkable fraction of waking life engaged in acts of "mental time travel". We dwell on our actions in the past and experience satisfaction or regret. More than mere…

cs.AI2018

Probing Physics Knowledge Using Tools from Developmental Psychology

Luis Piloto, Ari Weinstein, Dhruva TB +6

In order to build agents with a rich understanding of their environment, one key objective is to endow them with a grasp of intuitive physics; an ability to reason about three-dime…