README.md

metadata

license: gpl-2.0
configs:
  - config_name: alfworld
    data_files:
      - split: test
        path:
          - data/alfworld/test.jsonl
  - config_name: scienceworld
    data_files:
      - split: test
        path:
          - data/scienceworld/test.jsonl
  - config_name: babyai
    data_files:
      - split: test
        path:
          - data/babyai/test.jsonl
  - config_name: jericho
    data_files:
      - split: test
        path:
          - data/jericho/test.jsonl
  - config_name: pddl
    data_files:
      - split: test
        path:
          - data/pddl/test.jsonl
  - config_name: webarena
    data_files:
      - split: test
        path:
          - data/webarena/test.jsonl
  - config_name: webshop
    data_files:
      - split: test
        path:
          - data/webshop/test.jsonl
  - config_name: tool-query
    data_files:
      - split: test
        path:
          - data/tool-query/test.jsonl
  - config_name: tool-operation
    data_files:
      - split: test
        path:
          - data/tool-operation/test.jsonl
language:
  - en
tags:
  - Embodied AI
  - Game
  - Web
  - Tool
size_categories:
  - 1K<n<10K
task_categories:
  - text-generation
pretty_name: AgentBoard

AgentBoard: An Analytical Evaluation Board of Multi-turn LLM Agents

This is the official dataset repository of AgentBoard.

1. Data Overview

AgentBoard is composed of 9 diverse tasks which can be divided into 4 types, including Embodied AI, Game, Web, and Tool:

Embodied AI	Game	Web	Tool
AlfWorld ScienceWorld BabyAI	Jericho PDDL	WebShop WebArena	Tool-Query Tool-Operation

And statistics of the evaluation data of 9 environments are as follows:

	AlfWorld	ScienceWorld	BabyAI	Jericho	PDDL	WebShop	WebArena	Tool-Query	Tool-Operation
#Environment	134	90	112	20	60	251	245	60	40
#Turn	6	15	10	20	20	3	25	5	6
#Action Space	13	21	8	150	8	2	12	15	16
#Context Length	900	2800	1800	1500	2700	1200	15000	2100	4300
Progress Rate	subgoal	subgoal	subgoal	subgoal	match	match	match	subgoal	subgoal/match
#Avg. Subgoals	3	5	4	6	6	4	6	5	5
Hard/Easy Cutoff	3	3	3	4	6	1	4	4	4

To help researchers quickly understand evaluation data of each task, we provide Dataset Viewer at Huggingface Dataset: 🤗 AgentBoard.

Note: Please download the dataset from the link provided below for the reason that the data in Dataset Viewer is not complete.

2. Download Link

You can download the whole evaluation data by running the following command:

wget https://huggingface.co/datasets/hkust-nlp/agentboard/resolve/main/data.tar.gz

Please uncommpress the file and move the data to AgentBoard/data.

cd AgentBoard
mkdir data
tar -zxvf data.tar.gz

The file structure of evaluation data is as follows:

Click to expand the file structure

data
├── alfworld
│   ├── alfred.pddl # additional data for alfworld
│   ├── alfred.twl2 # additional data for alfworld
│   ├── json_2.1.1  # additional data for alfworld
│   └── test.jsonl
├── babyai
│   └── test.jsonl
├── jericho
│   ├── test.jsonl
│   └── z-machine-games-master  # additional data for jericho
├── pddl
│   └── test.jsonl
├── scienceworld
│   └── test.jsonl
├── tool-operation
│   └── test.jsonl
├── tool-query
│   ├── academia  # additional data for academia tool
│   └── test.jsonl
├── webarena
│   └── test.jsonl
└── webshop
    └── test.jsonl

3. Data Fields

We take an instance from the ScienceWorld task as an example to illustrate the data fields of evaluation data.

{
  "task": "scienceworld",
  "id": 0,
  "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.",
  "subgoals": ["You move to the outside.", "You focus on the crocodile egg."],
  "difficulty": "easy",
  "additional_info": {"var": 5, "env_name": "lifespan-longest-lived"}
}

Details of the data fields are as follows:

Field Name	Description
task	The task name of the example, e.g. alfworld, babyai, jericho, pddl, scienceworld, tool-operation, tool-query, webarena, webshop.
id	The id of the example.
goal	The goal of the example.
subgoals	The subgoals of the example.
difficulty	The difficulty of the example, e.g. easy, hard.
additional_info	The additional information of the example, each example has its own additional information.

4. Citation

@misc{ma2024agentboard,
      title={AgentBoard: An Analytical Evaluation Board of Multi-turn LLM Agents}, 
      author={Chang Ma and Junlei Zhang and Zhihao Zhu and Cheng Yang and Yujiu Yang and Yaohui Jin and Zhenzhong Lan and Lingpeng Kong and Junxian He},
      year={2024},
      eprint={2401.13178},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}