Update README.md

README.md

@@ -11,19 +11,19 @@ model-index:
   results:
   - metrics:
     - type: FAS (J=1)
-      value: 0.4419 ± 0.025996
+      value: 0.070768 ± 0.011055
       name: FAS
     - type: FAS (J=2)
-      value: 0.423547 ± 0.026536
+      value: 0.083818 ± 0.025049
       name: FAS
     - type: FAS (J=4)
-      value: 0.497902 ± 0.034868
+      value: 0.137035 ± 0.042001
       name: FAS
     - type: FAS (J=8)
-      value: 0.489516 ± 0.044905
+      value: 0.232737 ± 0.065282
       name: FAS
     - type: FAS (J=16)
-      value: 0.32623 ± 0.053239
+      value: 0.150935 ± 0.043573
       name: FAS
     task:
       type: OpenAI Gym
@@ -36,57 +36,17 @@ model-index:
 ---
 # Soft-Actor-Critic: Walker2d-v2
 
-These are 25 trained models over **seeds (0-4)**  and **J = 1, 2, 4, 8, 16** of **Soft actor critic** agent playing **Walker2d-v2** for **[Sequence Reinforcement Learning (SRL)](https://github.com/dee0512/Sequence-Reinforcement-Learning)**.
+These are 25 trained models over **seeds (0-4)** and **J = 1, 2, 4, 8, 16** of a **Soft Actor Critic (SAC)** agent playing **Walker2d-v2** from **[Sequence Reinforcement Learning (SRL)](https://github.com/dee0512/Sequence-Reinforcement-Learning)**.
 
 ## Model Sources
 
 **Repository:** [https://github.com/dee0512/Sequence-Reinforcement-Learning](https://github.com/dee0512/Sequence-Reinforcement-Learning)  
 **Paper (ICLR):** [https://openreview.net/forum?id=w3iM4WLuvy](https://openreview.net/forum?id=w3iM4WLuvy)  
-**Arxiv:** [arxiv.org/pdf/2410.08979](https://arxiv.org/pdf/2410.08979)
+**Arxiv:** [https://arxiv.org/pdf/2410.08979](https://arxiv.org/pdf/2410.08979)
 
-# Training Details:
-Using the repository:
-
-```
-python .\train_sac.py --env_name <env_name> --seed <seed> --j <j>
-```
-
-# Evaluation:
+## Training Details
 
-Download the models folder and place it in the same directory as the cloned repository. 
 Using the repository:
 
-```
-python .\eval_sac.py --env_name <env_name> --seed <seed> --j <j>
-```
-
-## Metrics:
-
-**FAS:** Frequency Averaged Score  
-**j:** Action repetition parameter
-
-
-# Citation
-
-The paper can be cited with the following bibtex entry:
-
-## BibTeX:
-
-```
-@inproceedings{DBLP:conf/iclr/PatelS25,
-  author       = {Devdhar Patel and
-                  Hava T. Siegelmann},
-  title        = {Overcoming Slow Decision Frequencies in Continuous Control: Model-Based
-                  Sequence Reinforcement Learning for Model-Free Control},
-  booktitle    = {The Thirteenth International Conference on Learning Representations,
-                  {ICLR} 2025, Singapore, April 24-28, 2025},
-  publisher    = {OpenReview.net},
-  year         = {2025},
-  url          = {https://openreview.net/forum?id=w3iM4WLuvy}
-}
-```
-
-## APA:
-```
-Patel, D., & Siegelmann, H. T. Overcoming Slow Decision Frequencies in Continuous Control: Model-Based Sequence Reinforcement Learning for Model-Free Control. In The Thirteenth International Conference on Learning Representations.
-```
+```bash
+python ./train_sac.py --env_name Walker2d-v2 --seed <seed> --j <j>