activity
20172026
most citedHybrid Reward Architecture for Reinforcement Learning

187 citations · 287 across the 5 of their papers we have counts for

collaborators

5 papers

cs.AI2026

MemWM: Memory-Augmented Text-Based World Model

Yujun Wang, Tao Zhang, Jinhe Bi +9

World models are increasingly used to support planning in agents by predicting how environment states evolve in response to agent actions. Yet fluent next-state predictions can sti…

cs.SE2022★ 2 cited

Towards Understanding Barriers and Mitigation Strategies of Software Engineers with Non-traditional Educational and Occupational Backgrounds

Tavian Barnes, Ken Jen Lee, Cristina Tavares +2

The traditional path to a software engineering career usually involves a post-secondary diploma in Software Engineering, Computer Science, or a related field. However, many individ…

cs.LG2020★ 5 cited

Hide-and-Seek Privacy Challenge

James Jordon, Daniel Jarrett, Jinsung Yoon +7

The clinical time-series setting poses a unique combination of challenges to data modeling and sharing. Due to the high dimensionality of clinical time series, adequate de-identifi…

cs.LG2018★ 93 cited

TextWorld: A Learning Environment for Text-based Games

Marc-Alexandre Côté, Ákos Kádár, Xingdi Yuan +10

We introduce TextWorld, a sandbox learning environment for the training and evaluation of RL agents on text-based games. TextWorld is a Python library that handles interactive play…

cs.LG2017★ 187 cited

Hybrid Reward Architecture for Reinforcement Learning

Harm van Seijen, Mehdi Fatemi, Joshua Romoff +3

One of the main challenges in reinforcement learning (RL) is generalisation. In typical deep RL methods this is achieved by approximating the optimal value function with a low-dime…