
Robust Constrained Reinforcement Learning for Continuous Control with Model Misspecification
Many realworld physical control systems are required to satisfy constra...
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Balancing Constraints and Rewards with MetaGradient D4PG
Deploying Reinforcement Learning (RL) agents to solve realworld applica...
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An empirical investigation of the challenges of realworld reinforcement learning
Reinforcement learning (RL) has proven its worth in a series of artifici...
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Robust Reinforcement Learning for Continuous Control with Model Misspecification
We provide a framework for incorporating robustness  to perturbations ...
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Action Assembly: Sparse Imitation Learning for Text Based Games with Combinatorial Action Spaces
We propose a computationally efficient algorithm that combines compresse...
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Learn What Not to Learn: Action Elimination with Deep Reinforcement Learning
Learning how to act when there are many available actions in each state ...
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Reward Constrained Policy Optimization
Teaching agents to perform tasks using Reinforcement Learning is no easy...
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SoftRobust ActorCritic PolicyGradient
Robust Reinforcement Learning aims to derive an optimal behavior that ac...
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Unicorn: Continual Learning with a Universal, Offpolicy Agent
Some realworld domains are best characterized as a single task, but for...
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Learning Robust Options
Robust reinforcement learning aims to produce policies that have strong ...
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Situationally Aware Options
Hierarchical abstractions, also known as options  a type of temporally...
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Shallow Updates for Deep Reinforcement Learning
Deep reinforcement learning (DRL) methods such as the Deep QNetwork (DQ...
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Situational Awareness by RiskConscious Skills
Hierarchical Reinforcement Learning has been previously shown to speed u...
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Adaptive Skills, Adaptive Partitions (ASAP)
We introduce the Adaptive Skills, Adaptive Partitions (ASAP) framework t...
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Iterative Hierarchical Optimization for Misspecified Problems (IHOMP)
For complex, highdimensional Markov Decision Processes (MDPs), it may b...
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CFORB: Circular FREAKORB Visual Odometry
We present a novel Visual Odometry algorithm entitled Circular FREAKORB...
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Bootstrapping Skills
The monolithic approach to policy representation in Markov Decision Proc...
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Daniel J. Mankowitz
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Research Scientist at DeepMind. Doctor of Philosophy (Ph.D.) Reinforcement Learning at Technion Israel Institute of Technology.