+SuReLI's recent research spans topics such as representation learning for RL [[ICLR2022]](https://arxiv.org/abs/2204.06355) [[NeurIPS2022]](https://arxiv.org/abs/2209.09203) [[NNLS2023]](https://arxiv.org/abs/2112.12980), RL in non-stationary MDPs [[AAAI2021]](https://arxiv.org/abs/2001.05411), evolutionary RL and optimization [[GECCO2021]](https://dl.acm.org/doi/abs/10.1145/3449639.3459361) [[GECCO2022]](https://dl.acm.org/doi/abs/10.1145/3512290.3528838), distillation of deep RL policies [[CoLLAs2022]](https://arxiv.org/abs/2210.02224), optimization for RL [[ICML2022]](https://arxiv.org/abs/2110.01528), neural architecture search [[AutoML2022]](https://proceedings.mlr.press/v188/maile22a), and applications to robotics, fluid flow control, software testing, video games, etc.
0 commit comments