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@T3AS

T3AS

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  1. MAD-ARL MAD-ARL Public

    Python project for the paper "Adversarial Deep Reinforcement Learning for Improving the Robustness of Multi-agent Autonomous Driving Policies".

    Python 6 2

  2. Benchmarking-QRS-2022 Benchmarking-QRS-2022 Public

    Implementation of "Evaluating the Robustness of Deep Reinforcement Learning for Autonomous Policies in a Multi-Agent Urban Driving Environment".

    Python 3 1

  3. ReMAV ReMAV Public

    Implementation of "ReMAV: Reward Modeling of Autonomous Vehicles for Finding Likely Failure Events".

    Jupyter Notebook 2 1

  4. DeepOrder-ICSME21 DeepOrder-ICSME21 Public

    Implementation of "DeepOrder: Deep Learning for Test Case Prioritization in Continuous Integration Testing".

    Jupyter Notebook 13 8

Repositories

Showing 4 of 4 repositories
  • ReMAV Public

    Implementation of "ReMAV: Reward Modeling of Autonomous Vehicles for Finding Likely Failure Events".

    Jupyter Notebook 2 GPL-3.0 1 0 0 Updated Sep 10, 2023
  • Benchmarking-QRS-2022 Public

    Implementation of "Evaluating the Robustness of Deep Reinforcement Learning for Autonomous Policies in a Multi-Agent Urban Driving Environment".

    Python 3 GPL-3.0 1 0 0 Updated Mar 31, 2023
  • MAD-ARL Public

    Python project for the paper "Adversarial Deep Reinforcement Learning for Improving the Robustness of Multi-agent Autonomous Driving Policies".

    Python 6 GPL-3.0 2 0 0 Updated Feb 24, 2023
  • DeepOrder-ICSME21 Public

    Implementation of "DeepOrder: Deep Learning for Test Case Prioritization in Continuous Integration Testing".

    Jupyter Notebook 13 GPL-3.0 8 0 0 Updated Jul 24, 2022

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