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07/06/2023
TGRL: An Algorithm for Teacher Guided Reinforcement Learning
Learning from rewards (i.e., reinforcement learning or RL) and learning ...
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06/09/2023
DDLP: Unsupervised Object-Centric Video Prediction with Deep Dynamic Latent Particles
We propose a new object-centric video prediction algorithm based on the ...
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06/05/2023
Explore to Generalize in Zero-Shot RL
We study zero-shot generalization in reinforcement learning - optimizing...
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06/04/2023
ContraBAR: Contrastive Bayes-Adaptive Deep RL
In meta reinforcement learning (meta RL), an agent seeks a Bayes-optimal...
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05/17/2023
Goal-Conditioned Supervised Learning with Sub-Goal Prediction
Recently, a simple yet effective algorithm – goal-conditioned supervised...
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03/01/2023
A Deep Learning Perspective on Network Routing
Routing is, arguably, the most fundamental task in computer networking, ...
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02/15/2023
Online Tool Selection with Learned Grasp Prediction Models
Deep learning-based grasp prediction models have become an industry stan...
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01/03/2023
Towards Deployable RL – What's Broken with RL Research and a Potential Fix
Reinforcement learning (RL) has demonstrated great potential, but is cur...
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11/03/2022
Learning Control by Iterative Inversion
We formulate learning for control as an inverse problem – inverting a dy...
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06/21/2022
Meta Reinforcement Learning with Finite Training Tasks – a Density Estimation Approach
In meta reinforcement learning (meta RL), an agent learns from a set of ...
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05/31/2022
Unsupervised Image Representation Learning with Deep Latent Particles
We propose a new representation of visual data that disentangles object ...
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11/01/2021
Validate on Sim, Detect on Real – Model Selection for Domain Randomization
A practical approach to learning robot skills, often termed sim2real, is...
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09/24/2021
Regularization Guarantees Generalization in Bayesian Reinforcement Learning through Algorithmic Stability
In the Bayesian reinforcement learning (RL) setting, a prior distributio...
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05/10/2021
Efficient Self-Supervised Data Collection for Offline Robot Learning
A practical approach to robot reinforcement learning is to first collect...
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03/20/2021
Unsupervised Feature Learning for Manipulation with Contrastive Domain Randomization
Robotic tasks such as manipulation with visual inputs require image feat...
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12/24/2020
Soft-IntroVAE: Analyzing and Improving the Introspective Variational Autoencoder
The recently introduced introspective variational autoencoder (IntroVAE)...
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10/07/2020
Online Safety Assurance for Deep Reinforcement Learning
Recently, deep learning has been successfully applied to a variety of ne...
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09/20/2020
Robust 2D Assembly Sequencing via Geometric Planning with Learned Scores
To compute robust 2D assembly plans, we present an approach that combine...
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08/06/2020
Offline Meta Reinforcement Learning
Consider the following problem, which we term Offline Meta Reinforcement...
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07/10/2020
Efficient MDP Analysis for Selfish-Mining in Blockchains
A proof of work (PoW) blockchain protocol distributes rewards to its par...
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02/27/2020
Hallucinative Topological Memory for Zero-Shot Visual Planning
In visual planning (VP), an agent learns to plan goal-directed behavior ...
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02/27/2020
Sub-Goal Trees – a Framework for Goal-Based Reinforcement Learning
Many AI problems, in robotics and other domains, are goal-based, essenti...
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01/15/2020
Deep Residual Flow for Novelty Detection
The effective application of neural networks in the real-world relies on...
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11/12/2019
Deep Variational Semi-Supervised Novelty Detection
In anomaly detection (AD), one seeks to identify whether a test sample i...
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09/10/2019
Bayesian Relational Memory for Semantic Visual Navigation
We introduce a new memory architecture, Bayesian Relational Memory (BRM)...
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06/12/2019
Sub-Goal Trees -- a Framework for Goal-Directed Trajectory Prediction and Optimization
Many AI problems, in robotics and other domains, are goal-directed, esse...
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06/01/2019
Harnessing Reinforcement Learning for Neural Motion Planning
Motion planning is an essential component in most of today's robotic app...
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05/11/2019
Learning Robotic Manipulation through Visual Planning and Acting
Planning for robotic manipulation requires reasoning about the changes a...
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03/10/2019
Domain Randomization for Active Pose Estimation
Accurate state estimation is a fundamental component of robotic control....
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03/04/2019
Reinforcement Learning on Variable Impedance Controller for High-Precision Robotic Assembly
Precise robotic manipulation skills are desirable in many industrial set...
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01/29/2019
Multi Agent Reinforcement Learning with Multi-Step Generative Models
The dynamics between agents and the environment are an important compone...
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10/08/2018
Internet Congestion Control via Deep Reinforcement Learning
We present and investigate a novel and timely application domain for dee...
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09/28/2018
Learning and Planning with a Semantic Model
Building deep reinforcement learning agents that can generalize and adap...
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08/06/2018
Distributional Multivariate Policy Evaluation and Exploration with the Bellman GAN
The recently proposed distributional approach to reinforcement learning ...
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07/24/2018
Learning Plannable Representations with Causal InfoGAN
In recent years, deep generative models have been shown to 'imagine' con...
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05/20/2018
Safe Policy Learning from Observations
In this paper, we consider the problem of learning a policy by observing...
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03/20/2018
Learning Robotic Assembly from CAD
In this work, motivated by recent manufacturing trends, we investigate a...
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02/28/2018
Model-Ensemble Trust-Region Policy Optimization
Model-free reinforcement learning (RL) methods are succeeding in a growi...
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11/22/2017
Safer Classification by Synthesis
The discriminative approach to classification using deep neural networks...
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11/20/2017
Situationally Aware Options
Hierarchical abstractions, also known as options -- a type of temporally...
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08/24/2017
Learning Generalized Reactive Policies using Deep Neural Networks
We consider the problem of learning for planning, where knowledge acquir...
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06/07/2017
Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments
We explore deep reinforcement learning methods for multi-agent domains. ...
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05/21/2017
Shallow Updates for Deep Reinforcement Learning
Deep reinforcement learning (DRL) methods such as the Deep Q-Network (DQ...
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10/10/2016
Situational Awareness by Risk-Conscious Skills
Hierarchical Reinforcement Learning has been previously shown to speed u...
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09/28/2016
Learning from the Hindsight Plan -- Episodic MPC Improvement
Model predictive control (MPC) is a popular control method that has prov...
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09/14/2016
Bayesian Reinforcement Learning: A Survey
Bayesian methods for machine learning have been widely investigated, yie...
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02/09/2016
Value Iteration Networks
We introduce the value iteration network (VIN): a fully differentiable n...
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09/17/2015
Generalized Emphatic Temporal Difference Learning: Bias-Variance Analysis
We consider the off-policy evaluation problem in Markov decision process...
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08/14/2015
Emphatic TD Bellman Operator is a Contraction
Recently, SuttonMW15 introduced the emphatic temporal differences (ETD) ...
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06/06/2015
