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08/07/2023
Exploiting Generalization in Offline Reinforcement Learning via Unseen State Augmentations
Offline reinforcement learning (RL) methods strike a balance between exp...
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05/23/2023
Proximal Policy Gradient Arborescence for Quality Diversity Reinforcement Learning
Training generally capable agents that perform well in unseen dynamic en...
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04/07/2023
Bridging Action Space Mismatch in Learning from Demonstrations
Learning from demonstrations (LfD) methods guide learning agents to a de...
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03/02/2023
Alexa Arena: A User-Centric Interactive Platform for Embodied AI
We introduce Alexa Arena, a user-centric simulation platform for Embodie...
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01/12/2023
Language-Informed Transfer Learning for Embodied Household Activities
For service robots to become general-purpose in everyday household envir...
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01/24/2022
Learning to Act with Affordance-Aware Multimodal Neural SLAM
Recent years have witnessed an emerging paradigm shift toward embodied a...
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10/28/2021
From Machine Learning to Robotics: Challenges and Opportunities for Embodied Intelligence
Machine learning has long since become a keystone technology, accelerati...
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09/16/2021
Decentralized Control of Quadrotor Swarms with End-to-end Deep Reinforcement Learning
We demonstrate the possibility of learning drone swarm controllers that ...
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08/10/2021
Embodied BERT: A Transformer Model for Embodied, Language-guided Visual Task Completion
Language-guided robots performing home and office tasks must navigate in...
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06/24/2021
Towards Exploiting Geometry and Time for Fast Off-Distribution Adaptation in Multi-Task Robot Learning
We explore possible methods for multi-task transfer learning which seek ...
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06/21/2020
Sample Factory: Egocentric 3D Control from Pixels at 100000 FPS with Asynchronous Reinforcement Learning
Increasing the scale of reinforcement learning experiments has allowed r...
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02/11/2020
Rapid Top-Down Synthesis of Large-Scale IoT Networks
Advances in optimization and constraint satisfaction techniques, togethe...
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01/24/2020
Encoding Physical Constraints in Differentiable Newton-Euler Algorithm
The recursive Newton-Euler Algorithm (RNEA) is a popular technique in ro...
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06/12/2019
Meta-Learning via Learned Loss
We present a meta-learning approach based on learning an adaptive, high-...
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01/04/2019
Accelerating Goal-Directed Reinforcement Learning by Model Characterization
We propose a hybrid approach aimed at improving the sample efficiency in...
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01/04/2019
Solving Markov Decision Processes with Reachability Characterization from Mean First Passage Times
A new mechanism for efficiently solving the Markov decision processes (M...
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01/03/2019
Reachability and Differential based Heuristics for Solving Markov Decision Processes
The solution convergence of Markov Decision Processes (MDPs) can be acce...
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10/04/2018
Zero-Shot Skill Composition and Simulation-to-Real Transfer by Learning Task Representations
Simulation-to-real transfer is an important strategy for making reinforc...
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09/26/2018
Scaling simulation-to-real transfer by learning composable robot skills
We present a novel solution to the problem of simulation-to-real transfe...
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07/04/2018
Region Growing Curriculum Generation for Reinforcement Learning
Learning a policy capable of moving an agent between any two states in t...
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08/09/2014