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07/21/2023
Hindsight-DICE: Stable Credit Assignment for Deep Reinforcement Learning
Oftentimes, environments for sequential decision-making problems can be ...
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05/19/2023
Shattering the Agent-Environment Interface for Fine-Tuning Inclusive Language Models
A centerpiece of the ever-popular reinforcement learning from human feed...
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05/05/2023
Bayesian Reinforcement Learning with Limited Cognitive Load
All biological and artificial agents must learn and make decisions given...
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12/24/2022
Inclusive Artificial Intelligence
Prevailing methods for assessing and comparing generative AIs incentiviz...
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10/30/2022
On Rate-Distortion Theory in Capacity-Limited Cognition Reinforcement Learning
Throughout the cognitive-science literature, there is widespread agreeme...
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10/30/2022
Planning to the Information Horizon of BAMDPs via Epistemic State Abstraction
The Bayes-Adaptive Markov Decision Process (BAMDP) formalism pursues the...
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06/04/2022
Deciding What to Model: Value-Equivalent Sampling for Reinforcement Learning
The quintessential model-based reinforcement-learning agent iteratively ...
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06/04/2022
Between Rate-Distortion Theory Value Equivalence in Model-Based Reinforcement Learning
The quintessential model-based reinforcement-learning agent iteratively ...
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10/26/2021
The Value of Information When Deciding What to Learn
All sequential decision-making agents explore so as to acquire knowledge...
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10/07/2021
Bad-Policy Density: A Measure of Reinforcement Learning Hardness
Reinforcement learning is hard in general. Yet, in many specific environ...
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03/10/2021
An Information-Theoretic Perspective on Credit Assignment in Reinforcement Learning
How do we formalize the challenge of credit assignment in reinforcement ...
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01/15/2021
Deciding What to Learn: A Rate-Distortion Approach
Agents that learn to select optimal actions represent a prominent focus ...
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10/05/2020
Randomized Value Functions via Posterior State-Abstraction Sampling
State abstraction has been an essential tool for dramatically improving ...
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06/18/2020
Reparameterized Variational Divergence Minimization for Stable Imitation
While recent state-of-the-art results for adversarial imitation-learning...
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04/22/2020
Flexible and Efficient Long-Range Planning Through Curious Exploration
Identifying algorithms that flexibly and efficiently discover temporally...
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02/12/2019
Deep Reinforcement Learning from Policy-Dependent Human Feedback
To widen their accessibility and increase their utility, intelligent age...
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12/03/2018
Mitigating Planner Overfitting in Model-Based Reinforcement Learning
An agent with an inaccurate model of its environment faces a difficult c...
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07/26/2017
A Tale of Two DRAGGNs: A Hybrid Approach for Interpreting Action-Oriented and Goal-Oriented Instructions
Robots operating alongside humans in diverse, stochastic environments mu...
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06/02/2017
Latent Attention Networks
Deep neural networks are able to solve tasks across a variety of domains...
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04/21/2017