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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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11/02/2022
Behavior Prior Representation learning for Offline Reinforcement Learning
Offline reinforcement learning (RL) struggles in environments with rich ...
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11/01/2022
Discrete Factorial Representations as an Abstraction for Goal Conditioned Reinforcement Learning
Goal-conditioned reinforcement learning (RL) is a promising direction fo...
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06/02/2022
Expressiveness and Learnability: A Unifying View for Evaluating Self-Supervised Learning
We propose a unifying view to analyze the representation quality of self...
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06/02/2022
Incorporating Explicit Uncertainty Estimates into Deep Offline Reinforcement Learning
Most theoretically motivated work in the offline reinforcement learning ...
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06/02/2022
When does return-conditioned supervised learning work for offline reinforcement learning?
Several recent works have proposed a class of algorithms for the offline...
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05/27/2022
Non-Markovian policies occupancy measures
A central object of study in Reinforcement Learning (RL) is the Markovia...
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03/09/2022
One-Shot Learning from a Demonstration with Hierarchical Latent Language
Humans have the capability, aided by the expressive compositionality of ...
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02/15/2022
Beyond the Policy Gradient Theorem for Efficient Policy Updates in Actor-Critic Algorithms
In Reinforcement Learning, the optimal action at a given state is depend...
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02/14/2022
On the Chattering of SARSA with Linear Function Approximation
SARSA, a classical on-policy control algorithm for reinforcement learnin...
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11/04/2021
Global Optimality and Finite Sample Analysis of Softmax Off-Policy Actor Critic under State Distribution Mismatch
In this paper, we establish the global optimality and convergence rate o...
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09/29/2021
Batched Bandits with Crowd Externalities
In Batched Multi-Armed Bandits (BMAB), the policy is not allowed to be u...
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09/29/2021
Dr Jekyll and Mr Hyde: the Strange Case of Off-Policy Policy Updates
The policy gradient theorem states that the policy should only be update...
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09/13/2021
The Emergence of the Shape Bias Results from Communicative Efficiency
By the age of two, children tend to assume that new word categories are ...
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05/31/2021
Multi-Objective SPIBB: Seldonian Offline Policy Improvement with Safety Constraints in Finite MDPs
We study the problem of Safe Policy Improvement (SPI) under constraints ...
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10/02/2020
A Deeper Look at Discounting Mismatch in Actor-Critic Algorithms
We investigate the discounting mismatch in actor-critic algorithm implem...
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02/22/2020
Reinforcement Learning Framework for Deep Brain Stimulation Study
Malfunctioning neurons in the brain sometimes operate synchronously, rep...
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02/21/2020
Learning Dynamic Knowledge Graphs to Generalize on Text-Based Games
Playing text-based games requires skill in processing natural language a...
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10/21/2019
Building Dynamic Knowledge Graphs from Text-based Games
We are interested in learning how to update Knowledge Graphs (KG) from t...
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09/11/2019
Safe Policy Improvement with an Estimated Baseline Policy
Previous work has shown the unreliability of existing algorithms in the ...
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07/11/2019
Safe Policy Improvement with Soft Baseline Bootstrapping
Batch Reinforcement Learning (Batch RL) consists in training a policy us...
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03/03/2019
Scaling up budgeted reinforcement learning
Can we learn a control policy able to adapt its behaviour in real time s...
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11/19/2018
Decentralized Exploration in Multi-Armed Bandits
We consider the decentralized exploration problem: a set of players coll...
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06/29/2018
Counting to Explore and Generalize in Text-based Games
We propose a recurrent RL agent with an episodic exploration mechanism t...
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12/19/2017
Safe Policy Improvement with Baseline Bootstrapping
A common goal in Reinforcement Learning is to derive a good strategy giv...
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07/05/2017
The Complex Negotiation Dialogue Game
This position paper formalises an abstract model for complex negotiation...
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04/03/2017
Multi-Advisor Reinforcement Learning
We consider tackling a single-agent RL problem by distributing it to n l...
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01/30/2017
Reinforcement Learning Algorithm Selection
This paper formalises the problem of online algorithm selection in the c...
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12/15/2016
