Brett Daley

According to our database, Brett Daley authored at least 20 papers between 2015 and 2025.

Collaborative distances:

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

2025

An Analysis of Action-Value Temporal-Difference Methods That Learn State Values.

Brett Daley, Prabhat Nagarajan, Martha White, Marlos C. Machado

CoRR, July, 2025

Deep Reinforcement Learning with Gradient Eligibility Traces.

Esraa Elelimy, Brett Daley, Andrew Patterson, Marlos C. Machado, Adam White, Martha White

CoRR, July, 2025

2024

Compound Returns Reduce Variance in Reinforcement Learning.

Brett Daley, Martha White, Marlos C. Machado

CoRR, 2024

Demystifying the Recency Heuristic in Temporal-Difference Learning.

Brett Daley, Marlos C. Machado, Martha White

RLJ, 2024

Averaging n-step Returns Reduces Variance in Reinforcement Learning.

Brett Daley, Martha White, Marlos C. Machado

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

On Centralized Critics in Multi-Agent Reinforcement Learning.

Xueguang Lyu, Andrea Baisero, Yuchen Xiao, Brett Daley, Christopher Amato

J. Artif. Intell. Res., 2023

Trajectory-Aware Eligibility Traces for Off-Policy Reinforcement Learning.

Brett Daley, Martha White, Christopher Amato, Marlos C. Machado

Proceedings of the International Conference on Machine Learning, 2023

2022

Adaptive Tree Backup Algorithms for Temporal-Difference Reinforcement Learning.

Brett Daley, Isaac Chan

CoRR, 2022

Asymmetric DQN for partially observable reinforcement learning.

Andrea Baisero, Brett Daley, Christopher Amato

Proceedings of the Uncertainty in Artificial Intelligence, 2022

2021

Improving the Efficiency of Off-Policy Reinforcement Learning by Accounting for Past Decisions.

Brett Daley, Christopher Amato

CoRR, 2021

Virtual Replay Cache.

Brett Daley, Christopher Amato

CoRR, 2021

Human-Level Control without Server-Grade Hardware.

Brett Daley, Christopher Amato

CoRR, 2021

Investigating Alternatives to the Root Mean Square for Adaptive Gradient Methods.

Brett Daley, Christopher Amato

CoRR, 2021

Contrasting Centralized and Decentralized Critics in Multi-Agent Reinforcement Learning.

Xueguang Lyu, Yuchen Xiao, Brett Daley, Christopher Amato

Proceedings of the AAMAS '21: 20th International Conference on Autonomous Agents and Multiagent Systems, 2021

Stratified Experience Replay: Correcting Multiplicity Bias in Off-Policy Reinforcement Learning.

Brett Daley, Cameron Hickert, Christopher Amato

Proceedings of the AAMAS '21: 20th International Conference on Autonomous Agents and Multiagent Systems, 2021

2020

Expectigrad: Fast Stochastic Optimization with Robust Convergence Properties.

Brett Daley, Christopher Amato

CoRR, 2020

Belief-Grounded Networks for Accelerated Robot Learning under Partial Observability.

Hai Nguyen, Brett Daley, Xinchao Song, Christopher Amato, Robert Platt

Proceedings of the 4th Conference on Robot Learning, 2020

2019

Reconciling λ-Returns with Experience Replay.

Brett Daley, Christopher Amato

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018

Efficient Eligibility Traces for Deep Reinforcement Learning.

Brett Daley, Christopher Amato

CoRR, 2018

2015

NUPAR: A Benchmark Suite for Modern GPU Architectures.

Yash Ukidave, Fanny Nina Paravecino, Leiming Yu, Charu Kalra, Amir Momeni, Zhongliang Chen, Nick Materise, Brett Daley, Perhaad Mistry, David R. Kaeli

Proceedings of the 6th ACM/SPEC International Conference on Performance Engineering, Austin, TX, USA, January 31, 2015