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Update README.md
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README.md
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task_categories:
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- text-generation
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pretty_name: AgentBoard
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task_categories:
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- text-generation
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pretty_name: AgentBoard
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+
---
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[Logo of AgentBoard]()
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# Dataset Card for AgentBoard
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This is the official dataset repository of [AgentBoard]().
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## 1. Data Overview
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AgentBoard is composed of 9 diverse tasks which can be divided into 4 types, including **Embodied AI**, **Game**, **Web**, and **Tool**:
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<table align="center">
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<tbody>
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<tr align="center" valign="bottom">
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<td>
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<b>Embodied AI</b>
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</td>
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<td>
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<b>Game</b>
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</td>
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<td>
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<b>Web</b>
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</td>
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<td>
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<b>Tool</b>
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</td>
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</tr>
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<tr valign="top">
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<td>
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- AlfWorld
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- ScienceWorld
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- BabyAI
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</td>
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<td>
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- Jericho
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- PDDL
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</td>
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<td>
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- WebShop
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- WebArena
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</td>
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<td>
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- Tool-Query
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- Tool-Operation
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</td>
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</tr>
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</tbody>
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</table>
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And statistics of the evaluation data of 9 task are as follows:
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| | AlfWorld | ScienceWorld | BabyAI | Jericho | PDDL | WebShop | WebArena | Tool-Query | Tool-Operation |
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|-------|----------|--------------|--------|---------|------|---------|----------|------------|----------------|
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| **Metric** | PR/SR | PR/SR | PR/SR | PR/SR | PR/SR | Matching | Matching | PR/SR | PR/SR/Matching |
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| **\#Avg. Turn** | 6 | 15 | 10 | 20 | 20 | 3 | 25 | 5 | 6 |
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| **\#Avg. Action Space** | 13 | 21 | 8 | 150 | 8 | 2 | 12 | 15 | 16 |
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| **\#Avg. Context Length** | 900 | 2800 | 1800 | 1500 | 2700 | 1200 | 15000 | 2100 | 4300 |
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| **\#Avg. Sub-goals** | 3 | 5 | 4 | 6 | 6 | 4 | 6 | 5 | 5 |
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| **\#Environment** | 134 | 90 | 112 | 20 | 60 | 251 | 245 | 60 | 40 |
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To help researchers quickly understand evaluation data of each task, we provide **Dataset Viewer** at Huggingface Dataset: [🤗 AgentBoard](https://huggingface.co/datasets/YANG-Cheng/alpaca).
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> Note: Please download the dataset from the link provided below for the reason that the data in Dataset Viewer is not complete.
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## 2. Download Link
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You can download the whole evaluation data by running the following command:
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```shell
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wget https://huggingface.co/datasets/YANG-Cheng/alpaca/resolve/main/data.tar.gz
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```
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Please uncommpress the file and move the data to `agent-board/data`.
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```shell
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cd agentboard
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mkdir data
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tar -zxvf data.tar.gz -C ./data
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```
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The file structure of evaluation data is as follows:
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<details>
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<summary>
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Click to expand the file structure
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</summary>
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```
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data
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├── alfworld
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│ ├── alfred.pddl # additional data for alfworld
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│ ├── alfred.twl2 # additional data for alfworld
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│ ├── json_2.1.1 # additional data for alfworld
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│ └── test.jsonl
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├── babyai
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│ └── test.jsonl
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├── jericho
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│ ├── test.jsonl
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│ └── z-machine-games-master # additional data for jericho
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├── pddl
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│ └── test.jsonl
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├── scienceworld
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│ └── test.jsonl
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├── tool-operation
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│ └── test.jsonl
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├── tool-query
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│ ├── academia # additional data for academia tool
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│ └── test.jsonl
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├── webarena
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│ └── test.jsonl
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└── webshop
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└── test.jsonl
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```
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</details>
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## 3. Data Fields
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We take an instance from the `ScienceWorld` task as an example to illustrate the data fields of evaluation data.
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```json
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{
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"task": "scienceworld",
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"id": 0,
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"goal": "Your task is to find the animal with the longest life span. The animals are in the 'outside' location. Focus on the animal with the longest life span.",
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"subgoals": ["You move to the outside.", "You focus on the crocodile egg."],
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"difficulty": "easy",
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"additional_info": {"var": 5, "env_name": "lifespan-longest-lived"}
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}
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```
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Details of the data fields are as follows:
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| Field Name | Description |
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|------------|-------------|
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| `task` | The task name of the example, e.g. `alfworld`, `babyai`, `jericho`, `pddl`, `scienceworld`, `tool-operation`, `tool-query`, `webarena`, `webshop`. |
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| `id` | The id of the example. |
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| `goal` | The goal of the example. |
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| `subgoals` | The subgoals of the example. |
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| `difficulty` | The difficulty of the example, e.g. `easy`, `hard`. |
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| `additional_info` | The additional information of the example, each example has its own additional information. |
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## 4. Citation
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```bibtex
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```
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