Update README.md

VAGEN is a multi-turn reinforcement learning framework designed specifically for training Vision-Language Model (VLM) Agents. Building upon existing approaches for LLM agents like RAGEN, Search-R1, and Agent-R1, VAGEN introduces enhancements that better handle the unique challenges of visual agents.

<img width="990" alt="image" src="https://github.com/user-attachments/assets/6220f4bd-5af0-4b0f-bf2f-198ac70c9023" />

## Key Innovations

VAGEN introduces the **Turn-aware Reason-Interaction Chain Optimization (TRICO)** algorithm which extends the traditional RICO approach with two key innovations:

- **with_loss_mask**: Whether to use gae mask to only calculate the gae of tokens output by the models

  - `rollout_manager.use_gae_mask=True`

 ## Cases

  We present several cases from the trained models with AICO and TRICO, as shown below.

### Cases from AICO Training

<img width="1107" alt="image (4)" src="https://github.com/user-attachments/assets/995ec921-faf8-4832-a4c0-1c2ce559a55c" />

![image (5)](https://github.com/user-attachments/assets/78bbc376-7e61-4a24-9911-eb28416eed37)

### Cases from TRICO Training

![image (6)](https://github.com/user-attachments/assets/60b251a2-e395-4079-a9aa-ceb4455b0a7a)

![image.png](attachment:38fb7b01-ffd8-407b-b1f1-4cd37ad18678:image.png)

 ## Limitations and Future Work