# Mode-Constrained Exploration for Model-Based Reinforcement Learning

Aidan Scannell

Sep 24, 2022reinforcement-learning
machine-learning
gaussian-processes
optimal-control
robotics
python
TensorFlow
GPflow
research

##### Aidan Scannell

###### Postdoctoral Researcher

My research interests include model-based reinforcement learning, probabilistic machine learning (gaussian processes, Bayesian neural networks, approximate Bayesian inference, etc), learning-based control and optimal control.

## Publications

We present a model-based RL algorithm that constrains training to a single dynamic mode with high probability. This is a difficult problem because the mode constraint is a hidden variable associated with the environment’s dynamics. As such, it is 1) unknown a priori and 2) we do not observe its output from the environment, so cannot learn it with supervised learning.

Aidan Scannell, Carl Henrik Ek, Arthur Richards

## Events

In this talk I’ll present our recent paper that has just been accepted into AISTATS 2023, titled Mode-Constrained Model-Based …

Feb 13, 2023 11:30 AM — 12:30 PM
University of Cambridge

Aidan Scannell