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Chargax: A JAX Accelerated EV Charging Simulator This paper introduces Chargax, a JAX-based environment for realistic simulation of electric vehicle charging stations designed for accelerated training of RL agents
GitHub - ponseko chargax Chargax: A JAX Accelerated EV Charging Simulator Note Please refer to the submission branch to reproduce results as presented in the paper The main branch ships the bare environment
RLJ · Chargax: A JAX Accelerated EV Charging Simulator This paper introduces Chargax, a JAX-based environment for realistic simulation of electric vehicle charging stations designed for accelerated training of RL agents
28 Chargax A JAX Accelerated E (i) This paper presents Chargax, an open-source EV charging environment written in JAX Context: Chargax could be used as a high-performance test bed for reinforcement
Chargax: A JAX Accelerated EV Charging Simulator - ADS This paper introduces Chargax, a JAX-based environment for realistic simulation of electric vehicle charging stations designed for accelerated training of RL agents
Chargax: A JAX Accelerated EV Charging Simulator - arXiv. org In this section, we demonstrate the use of Chargax across different included scenarios Additionally, we highlight performance improvements of Chargax compared to previous EV charging simulations Full details of the used model and configuration parameters, along with additional experimental results, can be found in Appendix B and D respectively
Chargax: A JAX Accelerated EV Charging Simulator | AI Research Paper . . . Chargax represents a pivotal advancement in electric vehicle charging simulation By dramatically reducing computational overhead and increasing simulation flexibility, it opens new possibilities for researchers and urban planners seeking to understand and optimize electric vehicle infrastructure
Chargax: A JAX Accelerated EV Charging Simulator This paper presents Chargax, an open-source EV charging environment written in JAX Context: Chargax could be used as a high-performance test bed for reinforcement learning benchmarking, or to develop better control algorithms for EV charging