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MoËT: Mixture of Expert Trees and its Application to Verifiable
  Reinforcement Learning

MoËT: Mixture of Expert Trees and its Application to Verifiable Reinforcement Learning

16 June 2019
Marko Vasic
Andrija Petrović
Kaiyuan Wang
Mladen Nikolic
Rishabh Singh
S. Khurshid
    OffRL
    MoE
ArXivPDFHTML

Papers citing "MoËT: Mixture of Expert Trees and its Application to Verifiable Reinforcement Learning"

3 / 3 papers shown
Title
Verifying Learning-Based Robotic Navigation Systems
Verifying Learning-Based Robotic Navigation Systems
Guy Amir
Davide Corsi
Raz Yerushalmi
Luca Marzari
D. Harel
Alessandro Farinelli
Guy Katz
94
37
0
26 May 2022
Learning Interpretable, High-Performing Policies for Autonomous Driving
Learning Interpretable, High-Performing Policies for Autonomous Driving
Rohan R. Paleja
Yaru Niu
Andrew Silva
Chace Ritchie
Sugju Choi
Matthew C. Gombolay
29
16
0
04 Feb 2022
Iterative Bounding MDPs: Learning Interpretable Policies via
  Non-Interpretable Methods
Iterative Bounding MDPs: Learning Interpretable Policies via Non-Interpretable Methods
Nicholay Topin
Stephanie Milani
Fei Fang
Manuela Veloso
OffRL
29
32
0
25 Feb 2021
1