ServiceNow Research

Reinforcement Learning

Mastering the Unsupervised Reinforcement Learning Benchmark from Pixels
Mastering the Unsupervised Reinforcement Learning Benchmark from Pixels
Controlling artificial agents from visual sensory data is an arduous task. Reinforcement learning (RL) algorithms can succeed but …
International Conference on Machine Learning (ICML),  2023.
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Choreographer: Learning and Adapting Skills in Imagination
Choreographer: Learning and Adapting Skills in Imagination
Unsupervised skill learning aims to learn a rich repertoire of behaviors without external supervision, providing artificial agents with …
International Conference of Learning Representations (ICLR),  2023.
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Deep Hyperbolic Reinforcement Learning for Continuous Control
Deep Hyperbolic Reinforcement Learning for Continuous Control
Integrating hyperbolic representations with Deep Reinforcement Learning (DRL) has recently been proposed as a promising approach for …
ICLR 2023, Tiny Papers,  2023.
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Leveraging Human Preferences to Master Poetry
Leveraging Human Preferences to Master Poetry
Large language models have been fine-tuned to learn poetry via supervised learning on a dataset containing relevant examples. However, …
AAAI Workshops,  2023.
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Haptics-based Curiosity for Sparse-reward Tasks
Haptics-based Curiosity for Sparse-reward Tasks
Robots in many real-world settings have access to force/torque sensors in their gripper and tactile sensing is often necessary in tasks …
Conference on Robot Learning (CoRL),  2022.
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Choreographer: Learning and Adapting Skills in Imagination
Choreographer: Learning and Adapting Skills in Imagination
Unsupervised skill learning aims to learn a rich repertoire of behaviors without external supervision, providing artificial agents with …
Workshop at the Neural Information Processing Systems (NeurIPS),  2022.
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Implicit Offline Reinforcement Learning via Supervised Learning
Implicit Offline Reinforcement Learning via Supervised Learning
Offline Reinforcement Learning (RL) via Supervised Learning is a simple and effective way to learn robotic skills from a dataset of …
Workshop at the Neural Information Processing Systems (NeurIPS),  2022.
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Using Confounded Data in Offline RL
Using Confounded Data in Offline RL
In this work we consider the problem of confounding in offline RL, also referred to as the delusion problem. While it is known that …
Workshop at the Neural Information Processing Systems (NeurIPS),  2022.
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Scaling up ML-based Black-box Planning with Partial STRIPS Models
Scaling up ML-based Black-box Planning with Partial STRIPS Models
A popular approach for sequential decision-making is to perform simulator-based search guided with Machine Learning (ML) methods like …
Workshop at International Join Conference on Artificial Intelligence (IJCAI),  2022.
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Direct Behavior Specification via Constrained Reinforcement Learning
Direct Behavior Specification via Constrained Reinforcement Learning
The standard formulation of Reinforcement Learning lacks a practical way of specifying what are admissible and forbidden behaviors. …
International Conference on Machine Learning (ICML),  2022.
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