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01/26/2023
Trajectory-Aware Eligibility Traces for Off-Policy Reinforcement Learning
Off-policy learning from multistep returns is crucial for sample-efficie...
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06/04/2022
Adaptive Tree Backup Algorithms for Temporal-Difference Reinforcement Learning
Q(σ) is a recently proposed temporal-difference learning method that int...
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12/23/2021
Improving the Efficiency of Off-Policy Reinforcement Learning by Accounting for Past Decisions
Off-policy learning from multistep returns is crucial for sample-efficie...
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12/06/2021
Virtual Replay Cache
Return caching is a recent strategy that enables efficient minibatch tra...
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11/01/2021
Human-Level Control without Server-Grade Hardware
Deep Q-Network (DQN) marked a major milestone for reinforcement learning...
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06/10/2021
Investigating Alternatives to the Root Mean Square for Adaptive Gradient Methods
Adam is an adaptive gradient method that has experienced widespread adop...
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02/22/2021
Stratified Experience Replay: Correcting Multiplicity Bias in Off-Policy Reinforcement Learning
Deep Reinforcement Learning (RL) methods rely on experience replay to ap...
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02/08/2021
Contrasting Centralized and Decentralized Critics in Multi-Agent Reinforcement Learning
Centralized Training for Decentralized Execution, where agents are train...
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10/19/2020
Belief-Grounded Networks for Accelerated Robot Learning under Partial Observability
Many important robotics problems are partially observable in the sense t...
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10/03/2020
Expectigrad: Fast Stochastic Optimization with Robust Convergence Properties
Many popular adaptive gradient methods such as Adam and RMSProp rely on ...
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10/23/2018
