Update Conference-on-Robot-Learning_CoRL.md

Author: GuochenZhou

Conference-on-Robot-Learning_CoRL.md

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 # CoRL (Conference on Robot Learning)
 
+* Antonova, R., Yang, J., Jatavallabhula K.M., Bohg, J., 2023, March. Rethinking optimization with differentiable simulation from a global perspective. In Conference on Robot Learning (pp. 276-286). PMLR. [ [www](https://proceedings.mlr.press/v205/antonova23a.html) | [pdf](https://proceedings.mlr.press/v205/antonova23a/antonova23a.pdf) ] ( **CMA-ES** )
+* Wochner, I., Schumacher, P., Martius, G., Büchler, D., Schmitt, S., & Haeufle, D., 2023, March. Learning with muscles: Benefits for data-efficiency and robustness in anthropomorphic tasks. In Conference on Robot Learning (pp. 1178-1188). PMLR. [ [www](https://proceedings.mlr.press/v205/wochner23a.html) | [pdf](https://proceedings.mlr.press/v205/wochner23a/wochner23a.pdf) ] ( **CMA-ES** )
+* Yang, Y., Zhang, T., Coumans, E., Tan, J., & Boots, B., 2022, January. Fast and efficient locomotion via learned gait transitions. In Conference on robot learning (pp. 773-783). PMLR. [ [www](https://proceedings.mlr.press/v164/yang22d.html) | [pdf](https://proceedings.mlr.press/v164/yang22d/yang22d.pdf) ] ( **CMA-ES** )
+* Niu, B., Wang, C., & Liu, C., 2021, October. Tolerance-guided policy learning for adaptable and transferrable delicate industrial insertion. In Conference on Robot Learning (pp. 2030-2039). PMLR.. [ [www](https://proceedings.mlr.press/v155/niu21a.html) | [pdf](https://proceedings.mlr.press/v155/niu21a/niu21a.pdf) ] ( **CMA-ES** )
 * Luck, K.S., Amor, H.B. and Calandra, R., 2020, May. Data-efficient co-adaptation of morphology and behaviour with deep reinforcement learning. In Conference on Robot Learning (pp. 854-869). PMLR. [ [www](http://proceedings.mlr.press/v100/luck20a.html) | [pdf](http://proceedings.mlr.press/v100/luck20a/luck20a.pdf) | [website](https://sites.google.com/view/drl-coadaptation) | [Python](https://github.com/ksluck/Coadaptation) ] (**PSO** | **CMA-ES**)
 * Ebrahimi, S., Rohrbach, A. and Darrell, T., 2017, October. Gradient-free policy architecture search and adaptation. In Conference on Robot Learning (pp. 505-514). PMLR. [ [www](http://proceedings.mlr.press/v78/ebrahimi17a.html) | [pdf](http://proceedings.mlr.press/v78/ebrahimi17a/ebrahimi17a.pdf) ] ( **ES** )