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07/24/2023
Parallel Q-Learning: Scaling Off-policy Reinforcement Learning under Massively Parallel Simulation
Reinforcement learning is time-consuming for complex tasks due to the ne...
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07/11/2023
Neuro-Inspired Efficient Map Building via Fragmentation and Recall
Animals and robots navigate through environments by building and refinin...
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07/06/2023
TGRL: An Algorithm for Teacher Guided Reinforcement Learning
Learning from rewards (i.e., reinforcement learning or RL) and learning ...
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06/22/2023
Harnessing Mixed Offline Reinforcement Learning Datasets via Trajectory Weighting
Most offline reinforcement learning (RL) algorithms return a target poli...
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04/27/2023
Decentralized Inference via Capability Type Structures in Cooperative Multi-Agent Systems
This work studies the problem of ad hoc teamwork in teams composed of ag...
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11/14/2022
Redeeming Intrinsic Rewards via Constrained Optimization
State-of-the-art reinforcement learning (RL) algorithms typically use ra...
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10/17/2022
Model Predictive Control via On-Policy Imitation Learning
In this paper, we leverage the rapid advances in imitation learning, a t...
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03/29/2022
Topological Experience Replay
State-of-the-art deep Q-learning methods update Q-values using state tra...
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03/14/2022
Stubborn: A Strong Baseline for Indoor Object Navigation
We present a strong baseline that surpasses the performance of previousl...
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05/30/2021
Reducing the Deployment-Time Inference Control Costs of Deep Reinforcement Learning Agents via an Asymmetric Architecture
Deep reinforcement learning (DRL) has been demonstrated to provide promi...
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07/16/2020
Mixture of Step Returns in Bootstrapped DQN
The concept of utilizing multi-step returns for updating value functions...
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02/01/2020
Periodic Intra-Ensemble Knowledge Distillation for Reinforcement Learning
Off-policy ensemble reinforcement learning (RL) methods have demonstrate...
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08/15/2019
Model-based Lookahead Reinforcement Learning
Model-based Reinforcement Learning (MBRL) allows data-efficient learning...
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06/26/2018
Adversarial Exploration Strategy for Self-Supervised Imitation Learning
We present an adversarial exploration strategy, a simple yet effective i...
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02/13/2018
Diversity-Driven Exploration Strategy for Deep Reinforcement Learning
Efficient exploration remains a challenging research problem in reinforc...
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02/01/2018
Virtual-to-Real: Learning to Control in Visual Semantic Segmentation
Collecting training data from the physical world is usually time-consumi...
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12/21/2017
A Deep Policy Inference Q-Network for Multi-Agent Systems
We present DPIQN, a deep policy inference Q-network that targets multi-a...
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03/08/2017