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Data · dataset · 2025

Safe Gaussian distributed soft actor-critic (SGDSAC) algorithm

Listed in Teesside University Research Data Repository

We have proposed a novel distributional DRL algorithm called safe Gaussian distributed soft actor-critic (SGDSAC).

Description

Additionally, to facilitate the training of DRL-based energy management strategies for HEVs using Python and Simulink, we have provided a DLL-based DRL environment configuration solution. We make our approach openly available here to facilitate the reviewers' evaluation of our work.

The "log" folder contains the raw training data recorded by "TensorBoard" during algorithm training. You can convert these data into Excel files using the "LoggerVisualizer" function provided in each algorithm's code. Python environment: python 3.9.0 pytorch 2.1.2 pytorch-cuda 12.1 numpy 1.26.4 cvxopt 1.2.6 cvxpy 1.5.2 tensorboard 2.17.0 pandas 2.1.4 gym 0.26.2

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Provenance · 1 source records, 7 field assertions
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Teesside University Research Data Repositoryoai:data.mendeley.com/32sjzxtgk7.17 h agoJSON v1
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concepts[field].local:field:earth-environmentalmapping · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0
concepts[field].local:field:energymapping · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0
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