Steven James

According to our database, Steven James authored at least 24 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

MiDaS: a large-scale Minecraft dataset for non-natural image benchmarking.

David Torpey, Max Parkin, Jonah Alter, Richard Klein, Steven James

J. Electronic Imaging, 2024

2023

MinePlanner: A Benchmark for Long-Horizon Planning in Large Minecraft Worlds.

William Hill, Ireton Liu, Anita de Mello Koch, Damion Harvey, George Konidaris, Steven James

CoRR, 2023

Counting Reward Automata: Sample Efficient Reinforcement Learning Through the Exploitation of Reward Function Structure.

Tristan Bester, Benjamin Rosman, Steven James, Geraud Nangue Tasse

CoRR, 2023

LLMatic: Neural Architecture Search via Large Language Models and Quality-Diversity Optimization.

Muhammad Umair Nasir, Sam Earle, Julian Togelius, Steven James, Christopher W. Cleghorn

CoRR, 2023

ROSARL: Reward-Only Safe Reinforcement Learning.

Geraud Nangue Tasse, Tamlin Love, Mark Nemecek, Steven James, Benjamin Rosman

CoRR, 2023

Hierarchically Composing Level Generators for the Creation of Complex Structures.

Michael Beukman, Manuel Fokam, Marcel Kruger, Guy Axelrod, Muhammad Umair Nasir, Branden Ingram, Benjamin Rosman, Steven James

CoRR, 2023

Dynamics Generalisation in Reinforcement Learning via Adaptive Context-Aware Policies.

Michael Beukman, Devon Jarvis, Richard Klein, Steven James, Benjamin Rosman

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Overlooked Implications of the Reconstruction Loss for VAE Disentanglement.

Nathan Michlo, Richard Klein, Steven James

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Augmentative Topology Agents For Open-Ended Learning.

Muhammad Umair Nasir, Michael Beukman, Steven James, Christopher W. Cleghorn

Proceedings of the Companion Proceedings of the Conference on Genetic and Evolutionary Computation, 2023

Synthesizing Navigation Abstractions for Planning with Portable Manipulation Skills.

Eric Rosen, Steven James, Sergio Orozco, Vedant Gupta, Max Merlin, Stefanie Tellex, George Konidaris

Proceedings of the Conference on Robot Learning, 2023

2022

Combining Evolutionary Search with Behaviour Cloning for Procedurally Generated Content.

Nicholas Muir, Steven James

CoRR, 2022

World Value Functions: Knowledge Representation for Learning and Planning.

Geraud Nangue Tasse, Benjamin Rosman, Steven James

CoRR, 2022

Skill Machines: Temporal Logic Composition in Reinforcement Learning.

Geraud Nangue Tasse, Devon Jarvis, Steven James, Benjamin Rosman

CoRR, 2022

Accounting for the Sequential Nature of States to Learn Features for Reinforcement Learning.

Nathan Michlo, Devon Jarvis, Richard Klein, Steven James

CoRR, 2022

Adaptive Online Value Function Approximation with Wavelets.

Michael Beukman, Michael Mitchley, Dean S. Wookey, Steven James, George Konidaris

CoRR, 2022

Data Overlap: A Prerequisite For Disentanglement.

Nathan Michlo, Steven James, Richard Klein

CoRR, 2022

Investigating Transfer Learning in Graph Neural Networks.

Nishai Kooverjee, Steven James, Terence L. van Zyl

CoRR, 2022

Towards Objective Metrics for Procedurally Generated Video Game Levels.

Michael Beukman, Steven James, Christopher W. Cleghorn

CoRR, 2022

Generalisation in Lifelong Reinforcement Learning through Logical Composition.

Geraud Nangue Tasse, Steven James, Benjamin Rosman

Proceedings of the Tenth International Conference on Learning Representations, 2022

Autonomous Learning of Object-Centric Abstractions for High-Level Planning.

Steven James, Benjamin Rosman, George Konidaris

Proceedings of the Tenth International Conference on Learning Representations, 2022

Procedural content generation using neuroevolution and novelty search for diverse video game levels.

Michael Beukman, Christopher W. Cleghorn, Steven James

Proceedings of the GECCO '22: Genetic and Evolutionary Computation Conference, Boston, Massachusetts, USA, July 9, 2022

2020

Quantisation and Pruning for Neural Network Compression and Regularisation.

Kimessha Paupamah, Steven James, Richard Klein

CoRR, 2020

Inter- and Intra-domain Knowledge Transfer for Related Tasks in Deep Character Recognition.

Nishai Kooverjee, Steven James, Terence L. van Zyl

CoRR, 2020

2018

Learning Portable Symbolic Representations.

Steven James

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018