activity
20182022
most citedHypernetworks in Meta-Reinforcement Learning

5 citations · 5 across the 3 of their papers we have counts for

collaborators

5 papers

cs.LG20225 cited

Hypernetworks in Meta-Reinforcement Learning

Jacob Beck, Matthew Thomas Jackson, Risto Vuorio +1

Training a reinforcement learning (RL) agent on a real-world robotics task remains generally impractical due to sample inefficiency. Multi-task RL and meta-RL aim to improve sample…

cs.LG2022

An Investigation of the Bias-Variance Tradeoff in Meta-Gradients

Risto Vuorio, Jacob Beck, Shimon Whiteson +2

Meta-gradients provide a general approach for optimizing the meta-parameters of reinforcement learning (RL) algorithms. Estimation of meta-gradients is central to the performance o…

cs.HC2019

Stackelberg Punishment and Bully-Proofing Autonomous Vehicles

Matt Cooper, Jun Ki Lee, Jacob Beck +7

Mutually beneficial behavior in repeated games can be enforced via the threat of punishment, as enshrined in game theory's well-known "folk theorem." There is a cost, however, to a…

cs.LG2019

ReNeg and Backseat Driver: Learning from Demonstration with Continuous Human Feedback

Jacob Beck, Zoe Papakipos, Michael Littman

In autonomous vehicle (AV) control, allowing mistakes can be quite dangerous and costly in the real world. For this reason we investigate methods of training an AV without allowing…

cs.LG2018

Neural Mesh: Introducing a Notion of Space and Conservation of Energy to Neural Networks

Jacob Beck, Zoe Papakipos

Neural networks are based on a simplified model of the brain. In this project, we wanted to relax the simplifying assumptions of a traditional neural network by making a model that…