2022 IEEE 61st Conference on Decision and Control (CDC) 2022
DOI: 10.1109/cdc51059.2022.9993030
|View full text |Cite
|
Sign up to set email alerts
|

Online greedy identification of linear dynamical systems

Abstract: Model-based reinforcement learning is a powerful tool, but collecting data to fit an accurate model of the system can be costly. Exploring an unknown environment in a sample-efficient manner is hence of great importance. However, the complexity of dynamics and the computational limitations of real systems make this task challenging. In this work, we introduce FLEX, an exploration algorithm for nonlinear dynamics based on optimal experimental design. Our policy maximizes the information of the next step and res… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

0
0
0

Year Published

2024
2024
2024
2024

Publication Types

Select...
1

Relationship

0
1

Authors

Journals

citations
Cited by 1 publication
references
References 30 publications
0
0
0
Order By: Relevance