Steven D. James

According to our database, Steven D. James authored at least 12 papers between 2017 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

Automatic encoding and repair of reactive high-level tasks with learned abstract representations.

Adam Pacheck, Steven D. James, George Dimitri Konidaris, Hadas Kress-Gazit

Int. J. Robotics Res., April, 2023

2022

World Value Functions: Knowledge Representation for Multitask Reinforcement Learning.

Geraud Nangue Tasse, Steven D. James, Benjamin Rosman

CoRR, 2022

Learning Abstract and Transferable Representations for Planning.

Steven D. James, Benjamin Rosman, George Dimitri Konidaris

CoRR, 2022

2021

Learning to Follow Language Instructions with Compositional Policies.

Vanya Cohen, Geraud Nangue Tasse, Nakul Gopalan, Steven D. James, Matthew C. Gombolay, Benjamin Rosman

CoRR, 2021

2020

If dropout limits trainable depth, does critical initialisation still matter? A large-scale statistical analysis on ReLU networks.

Arnu Pretorius, Elan Van Biljon, Benjamin van Niekerk, Ryan Eloff, Matthew Reynard, Steven D. James, Benjamin Rosman, Herman Kamper, Steve Kroon

Pattern Recognit. Lett., 2020

Learning Options from Demonstration using Skill Segmentation.

Matthew Cockcroft, Shahil Mawjee, Steven D. James, Pravesh Ranchod

CoRR, 2020

A Boolean Task Algebra for Reinforcement Learning.

Geraud Nangue Tasse, Steven D. James, Benjamin Rosman

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Learning Portable Representations for High-Level Planning.

Steven D. James, Benjamin Rosman, George Konidaris

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Multi-Pass Q-Networks for Deep Reinforcement Learning with Parameterised Action Spaces.

Craig J. Bester, Steven D. James, George Dimitri Konidaris

CoRR, 2019

Composing Value Functions in Reinforcement Learning.

Benjamin van Niekerk, Steven D. James, Adam Christopher Earle, Benjamin Rosman

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

Will it Blend? Composing Value Functions in Reinforcement Learning.

Benjamin van Niekerk, Steven D. James, Adam Christopher Earle, Benjamin Rosman

CoRR, 2018

2017

An Analysis of Monte Carlo Tree Search.

Steven D. James, George Dimitri Konidaris, Benjamin Rosman

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017