18 citations · 44 across the 5 of their papers we have counts for
6 papers
Disentangled Planning and Control in Vision Based Robotics via Reward Machines
Alberto Camacho, Jacob Varley, Deepali Jain +2
In this work we augment a Deep Q-Learning agent with a Reward Machine (DQRM) to increase speed of learning vision-based policies for robot tasks, and overcome some of the limitatio…
From Pixels to Legs: Hierarchical Learning of Quadruped Locomotion
Deepali Jain, Atil Iscen, Ken Caluwaerts
Legged robots navigating crowded scenes and complex terrains in the real world are required to execute dynamic leg movements while processing visual input for obstacle avoidance an…
Learning Agile Locomotion Skills with a Mentor
Atil Iscen, George Yu, Alejandro Escontrela +3
Developing agile behaviors for legged robots remains a challenging problem. While deep reinforcement learning is a promising approach, learning truly agile behaviors typically requ…
Reinforcement Learning with Chromatic Networks for Compact Architecture Search
Xingyou Song, Krzysztof Choromanski, Jack Parker-Holder +6
We present a neural architecture search algorithm to construct compact reinforcement learning (RL) policies, by combining ENAS and ES in a highly scalable and intuitive way. By def…
Hierarchical Reinforcement Learning for Quadruped Locomotion
Deepali Jain, Atil Iscen, Ken Caluwaerts
Legged locomotion is a challenging task for learning algorithms, especially when the task requires a diverse set of primitive behaviors. To solve these problems, we introduce a hie…
Provably Robust Blackbox Optimization for Reinforcement Learning
Krzysztof Choromanski, Aldo Pacchiano, Jack Parker-Holder +6
Interest in derivative-free optimization (DFO) and "evolutionary strategies" (ES) has recently surged in the Reinforcement Learning (RL) community, with growing evidence that they…