activity
20172023
most citedGeneralization in Reinforcement Learning with Selective Noise Injection and Information Bottleneck

58 citations · 215 across the 22 of their papers we have counts for

collaborators

25 papers

cs.AI2023★ 1 cited

Adaptive Scaffolding in Block-Based Programming via Synthesizing New Tasks as Pop Quizzes

Ahana Ghosh, Sebastian Tschiatschek, Sam Devlin +1

Block-based programming environments are increasingly used to introduce computing concepts to beginners. However, novice students often struggle in these environments, given the co…

cs.AI2023★ 23 cited

Imitating Human Behaviour with Diffusion Models

Tim Pearce, Tabish Rashid, Anssi Kanervisto +8

Diffusion models have emerged as powerful generative models in the text-to-image domain. This paper studies their application as observation-to-action models for imitating human be…

cs.HC2023★ 16 cited

Navigates Like Me: Understanding How People Evaluate Human-Like AI in Video Games

Stephanie Milani, Arthur Juliani, Ida Momennejad +7

We aim to understand how people assess human likeness in navigation produced by people and artificially intelligent (AI) agents in a video game. To this end, we propose a novel AI…

cs.LG2023★ 1 cited

Trust-Region-Free Policy Optimization for Stochastic Policies

Mingfei Sun, Benjamin Ellis, Anuj Mahajan +3

Trust Region Policy Optimization (TRPO) is an iterative method that simultaneously maximizes a surrogate objective and enforces a trust region constraint over consecutive policies…

cs.LG2023★ 2 cited

Contrastive Meta-Learning for Partially Observable Few-Shot Learning

Adam Jelley, Amos Storkey, Antreas Antoniou +1

Many contrastive and meta-learning approaches learn representations by identifying common features in multiple views. However, the formalism for these approaches generally assumes…

cs.LG2022★ 2 cited

UniMASK: Unified Inference in Sequential Decision Problems

Micah Carroll, Orr Paradise, Jessy Lin +8

Randomly masking and predicting word tokens has been a successful approach in pre-training language models for a variety of downstream tasks. In this work, we observe that the same…