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01/08/2023
Learning Symbolic Representations for Reinforcement Learning of Non-Markovian Behavior
Many real-world reinforcement learning (RL) problems necessitate learnin...
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11/20/2022
Noisy Symbolic Abstractions for Deep RL: A case study with Reward Machines
Natural and formal languages provide an effective mechanism for humans t...
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06/03/2022
Challenges to Solving Combinatorially Hard Long-Horizon Deep RL Tasks
Deep reinforcement learning has shown promise in discrete domains requir...
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12/17/2021
Learning Reward Machines: A Study in Partially Observable Reinforcement Learning
Reinforcement learning (RL) is a central problem in artificial intellige...
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06/04/2021
Be Considerate: Objectives, Side Effects, and Deciding How to Act
Recent work in AI safety has highlighted that in sequential decision mak...
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05/31/2021
AppBuddy: Learning to Accomplish Tasks in Mobile Apps via Reinforcement Learning
Human beings, even small children, quickly become adept at figuring out ...
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02/13/2021
LTL2Action: Generalizing LTL Instructions for Multi-Task RL
We address the problem of teaching a deep reinforcement learning (RL) ag...
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10/06/2020
Interpretable Sequence Classification via Discrete Optimization
Sequence classification is the task of predicting a class label given a ...
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10/06/2020
Reward Machines: Exploiting Reward Function Structure in Reinforcement Learning
Reinforcement learning (RL) methods usually treat reward functions as bl...
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10/05/2020
The act of remembering: a study in partially observable reinforcement learning
Reinforcement Learning (RL) agents typically learn memoryless policies—p...
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05/24/2017
