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06/05/2023
A Study of Global and Episodic Bonuses for Exploration in Contextual MDPs
Exploration in environments which differ across episodes has received in...
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10/12/2022
Semi-Supervised Offline Reinforcement Learning with Action-Free Trajectories
Natural agents can effectively learn from multiple data sources that dif...
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10/11/2022
Exploration via Elliptical Episodic Bonuses
In recent years, a number of reinforcement learning (RL) methods have be...
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07/16/2020
PC-PG: Policy Cover Directed Exploration for Provable Policy Gradient Learning
Direct policy gradient methods for reinforcement learning are a successf...
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11/13/2019
Kinematic State Abstraction and Provably Efficient Rich-Observation Reinforcement Learning
We present an algorithm, HOMER, for exploration and reinforcement learni...
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11/01/2019
Explicit Explore-Exploit Algorithms in Continuous State Spaces
We present a new model-based algorithm for reinforcement learning (RL) w...
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01/08/2019
Model-Predictive Policy Learning with Uncertainty Regularization for Driving in Dense Traffic
Learning a policy using only observational data is challenging because t...
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11/14/2017
Prediction Under Uncertainty with Error-Encoding Networks
In this work we introduce a new framework for performing temporal predic...
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05/19/2017
Model-Based Planning in Discrete Action Spaces
Planning actions using learned and differentiable forward models of the ...
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12/12/2016
Tracking the World State with Recurrent Entity Networks
We introduce a new model, the Recurrent Entity Network (EntNet). It is e...
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02/22/2016
Recurrent Orthogonal Networks and Long-Memory Tasks
Although RNNs have been shown to be powerful tools for processing sequen...
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06/16/2015
Deep Convolutional Networks on Graph-Structured Data
Deep Learning's recent successes have mostly relied on Convolutional Net...
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11/30/2014
The Loss Surfaces of Multilayer Networks
We study the connection between the highly non-convex loss function of a...
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12/20/2013
