Joshua Romoff

According to our database1, Joshua Romoff authored at least 19 papers between 2016 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2023
Minimax Exploiter: A Data Efficient Approach for Competitive Self-Play.
CoRR, 2023

Improving Intrinsic Exploration by Creating Stationary Objectives.
CoRR, 2023

Learning Computational Efficient Bots with Costly Features.
Proceedings of the IEEE Conference on Games, 2023

2022
Direct Behavior Specification via Constrained Reinforcement Learning.
Proceedings of the International Conference on Machine Learning, 2022

2021
Graph augmented Deep Reinforcement Learning in the GameRLand3D environment.
CoRR, 2021

Deep Reinforcement Learning for Navigation in AAA Video Games.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

TDprop: Does Adaptive Optimization With Jacobi Preconditioning Help Temporal Difference Learning?
Proceedings of the AAMAS '21: 20th International Conference on Autonomous Agents and Multiagent Systems, 2021

2020
TDprop: Does Jacobi Preconditioning Help Temporal Difference Learning?
CoRR, 2020

Towards the Systematic Reporting of the Energy and Carbon Footprints of Machine Learning.
CoRR, 2020

2019
Separating value functions across time-scales.
CoRR, 2019

Randomized Value Functions via Multiplicative Normalizing Flows.
Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

Gossip-based Actor-Learner Architectures for Deep Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Separable value functions across time-scales.
Proceedings of the 36th International Conference on Machine Learning, 2019

TarMAC: Targeted Multi-Agent Communication.
Proceedings of the 36th International Conference on Machine Learning, 2019

2018
Where Did My Optimum Go?: An Empirical Analysis of Gradient Descent Optimization in Policy Gradient Methods.
CoRR, 2018

Reward Estimation for Variance Reduction in Deep Reinforcement Learning.
Proceedings of the 2nd Annual Conference on Robot Learning, 2018

2017
Multi-Advisor Reinforcement Learning.
CoRR, 2017

Hybrid Reward Architecture for Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016
Improving Scalability of Reinforcement Learning by Separation of Concerns.
CoRR, 2016


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