Steven D. James

Publication Activity (10 Years)

Years Active: 2017-2023
Publications (10 Years): 15

Top Topics

Knowledge Representation

Statistical Analysis

Reinforcement Learning

Top Venues

Int. J. Robotics Res.

Publications

Adam Pacheck, Steven D. James, George Dimitri Konidaris, Hadas Kress-Gazit
Automatic encoding and repair of reactive high-level tasks with learned abstract representations. Int. J. Robotics Res. 42 (4-5) (2023)
Geraud Nangue Tasse, Steven D. James, Benjamin Rosman
World Value Functions: Knowledge Representation for Multitask Reinforcement Learning. CoRR (2022)
Steven D. James, Benjamin Rosman, George Dimitri Konidaris
Learning Abstract and Transferable Representations for Planning. CoRR (2022)
Vanya Cohen, Geraud Nangue Tasse, Nakul Gopalan, Steven D. James, Matthew C. Gombolay, Benjamin Rosman
Learning to Follow Language Instructions with Compositional Policies. CoRR (2021)
Geraud Nangue Tasse, Steven D. James, Benjamin Rosman
A Boolean Task Algebra for Reinforcement Learning. NeurIPS (2020)
Steven D. James, Benjamin Rosman, George Konidaris
Learning Portable Representations for High-Level Planning. ICML (2020)
Geraud Nangue Tasse, Steven D. James, Benjamin Rosman
A Boolean Task Algebra for Reinforcement Learning. CoRR (2020)
Arnu Pretorius, Elan Van Biljon, Benjamin van Niekerk, Ryan Eloff, Matthew Reynard, Steven D. James, Benjamin Rosman, Herman Kamper, Steve Kroon
If dropout limits trainable depth, does critical initialisation still matter? A large-scale statistical analysis on ReLU networks. Pattern Recognit. Lett. 138 (2020)
Matthew Cockcroft, Shahil Mawjee, Steven D. James, Pravesh Ranchod
Learning Options from Demonstration using Skill Segmentation. CoRR (2020)
Craig J. Bester, Steven D. James, George Dimitri Konidaris
Multi-Pass Q-Networks for Deep Reinforcement Learning with Parameterised Action Spaces. CoRR (2019)
Steven D. James, Benjamin Rosman, George Dimitri Konidaris
Learning Portable Representations for High-Level Planning. CoRR (2019)
Benjamin van Niekerk, Steven D. James, Adam Christopher Earle, Benjamin Rosman
Composing Value Functions in Reinforcement Learning. ICML (2019)
Arnu Pretorius, Elan Van Biljon, Benjamin van Niekerk, Ryan Eloff, Matthew Reynard, Steven D. James, Benjamin Rosman, Herman Kamper, Steve Kroon
If dropout limits trainable depth, does critical initialisation still matter? A large-scale statistical analysis on ReLU networks. CoRR (2019)
Benjamin van Niekerk, Steven D. James, Adam Christopher Earle, Benjamin Rosman
Will it Blend? Composing Value Functions in Reinforcement Learning. CoRR (2018)
Steven D. James, George Dimitri Konidaris, Benjamin Rosman
An Analysis of Monte Carlo Tree Search. AAAI (2017)