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Exploitation Exploration (in MBRL) | natolambert

Exploitation Exploration (in MBRL). A few lessons from model-based reinforcement learning how exploration can happen through exploitation of some metric. January 25, 2021. | Machine Learning.

Lambert - On the Importance of Hyperparameter Optimization for Model-based Reinforcement Learning

Model-based Reinforcement Learning (MBRL) is a promising framework for learning control in a data-efficient manner.

Lambert - MBRL-Lib: A Modular Library for Model-based Reinforcement Learning

MBRL-Lib: A Modular Library for Model-based Reinforcement Learning. Apr 20, 2021. | Luis Pineda, Brandon Amos, Amy Zhang, Nathan O Lambert, Roberto Calandra. Tags: ABSTRACT. : hide & show. ↓↑.

Lambert - Objective Mismatch in Model-based Reinforcement Learning

Model-based reinforcement learning (MBRL) is a powerful framework for data-efficiently learning control of continuous tasks.

Debugging Deep Model-based Reinforcement Learning Systems | natolambert

I saw an. example. of this debugging lessons for model-free RL and felt fairly obliged to repeat it for model-based RL (MBRL). Ultimately MBRL is so much younger and less pervasive, so if I want it to keep growing I need to invest that time in all of you.

Lambert - Investigating Compounding Prediction Errors in Learned Dynamics Models

Model-based reinforcement learning (MBRL) is one paradigm which relies on the iterative learning and prediction of state-action transitions to solve a task.

Lambert - Low Level Control of a Quadrotor with Deep Model-Based Reinforcement Learning

To address the challenge of rapidly generating low-level controllers, we argue for using model-based reinforcement learning (MBRL) trained on relatively small amounts of automatically generated (i.e. without system simulation) data.

Lambert - Nonholonomic Yaw Control of an Underactuated Flying Robot with Model-based Reinforcement Learning

Nonholonomic Yaw Control of an Underactuated Flying Robot with Model-based Reinforcement Learning. IEEE Robotics and Automation Letters. Dec 21, 2020. | Nathan Lambert, Craig Schindler, Daniel S Drew, Kristofer SJ Pister. Tags: ABSTRACT. : hide & show. ↓↑.

ML/RL & Microrobotics | natolambert

History: Model-based Reinforcement Learning (MBRL) as a case study. This is the level of the stack where I took a total leap of faith in the spring of 2018.

Lambert - Learning Accurate Long-term Dynamics for Model-based Reinforcement Learning

What you need to know: Current methods for predicting into the future of MBRL are not thematically matched with how they are used for control.