ScienceWorld: An interactive text environment to study AIagents on accomplishing tasks from the standardized elementary science curriculum.
Project description
ScienceWorld
ScienceWorld is a text-based virtual environment centered around accomplishing tasks from the standardized elementary science curriculum. This code accompanies the paper ScienceWorld: Is your Textual Agent Smarter than a 5th grader?.
Demo and examples
You can try ScienceWorld yourself via our HuggingFace Space or read some of the playthrough transcripts.
Citation
@misc{scienceworld2022,
title={ScienceWorld: Is your Agent Smarter than a 5th Grader?},
author={Ruoyao Wang and Peter Jansen and Marc-Alexandre C{\^o}t{\'e} and Prithviraj Ammanabrolu},
year={2022},
eprint={2203.07540},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2203.07540}
}
Quickstart
Before running: You will have to have Java 1.8+ installed on your system (shipped with most linux distributions) and Python 3.8+. We recommend creating a conda environment like this:
conda create --name scienceworld python=3.8
conda activate scienceworld
Then, install ScienceWorld either from PyPi:
pip install scienceworld
or from source in development mode:
git clone https://github.com/allenai/ScienceWorld.git
cd ScienceWorld
pip install .
Run an example random agent, on task 13 (classification: place a non-living thing in a box), for 5 episodes:
python examples/random_agent.py --task-num=13 --num-episodes=5 --simplifications-preset easy
Run a user console where you can interact with the environment, on task 3 (change of state: melting):
python examples/human.py --task-num=3 --num-episodes=5
Web Server Demo
A web server demo is also available, that allows running a ScienceWorld user console that can be interacted with in a web browser.
To run the web server demo:
conda create --name scienceworld python=3.8
conda activate scienceworld
pip install scienceworld[webserver]
Run the web server:
python examples/scienceworld-web-server-example.py
Point your web browser to:
localhost:8080
ScienceWorld Design
ScienceWorld is written in Scala (2.12.9), and compiles using sbt into a JAR file that is run with Java. For convenience, a Python API is provided (Python >= 3.8), which interfaces using the py4j package.
If you modified the Scala code, you can recompile the JAR file by running:
./simulator/package.sh
pip install -e .
Tasks
The tasks are listed in the table below along with their number of variations. Either the task ID or its name can be used to a task with env.load().
| Task ID | Task Name | # Variations |
|---|---|---|
| 1-1 | boil | 30 |
| 1-2 | melt | 30 |
| 1-3 | freeze | 30 |
| 1-4 | change-the-state-of-matter-of | 30 |
| 2-1 | use-thermometer | 540 |
| 2-2 | measure-melting-point-known-substance | 436 |
| 2-3 | measure-melting-point-unknown-substance | 300 |
| 3-1 | power-component | 20 |
| 3-2 | power-component-renewable-vs-nonrenewable-energy | 20 |
| 3-3 | test-conductivity | 900 |
| 3-4 | test-conductivity-of-unknown-substances | 600 |
| 4-1 | find-living-thing | 300 |
| 4-2 | find-non-living-thing | 300 |
| 4-3 | find-plant | 300 |
| 4-4 | find-animal | 300 |
| 5-1 | grow-plant | 126 |
| 5-2 | grow-fruit | 126 |
| 6-1 | chemistry-mix | 32 |
| 6-2 | chemistry-mix-paint-secondary-color | 36 |
| 6-3 | chemistry-mix-paint-tertiary-color | 36 |
| 7-1 | lifespan-longest-lived | 125 |
| 7-2 | lifespan-shortest-lived | 125 |
| 7-3 | lifespan-longest-lived-then-shortest-lived | 125 |
| 8-1 | identify-life-stages-1 | 14 |
| 8-2 | identify-life-stages-2 | 10 |
| 9-1 | inclined-plane-determine-angle | 168 |
| 9-2 | inclined-plane-friction-named-surfaces | 1386 |
| 9-3 | inclined-plane-friction-unnamed-surfaces | 162 |
| 10-1 | mendelian-genetics-known-plant | 120 |
| 10-2 | mendelian-genetics-unknown-plant | 480 |
Simplifications
ScienceWorld supports a number of simplifications that can be applied to the environment to make it easier for agents to learn. These simplifications can be applied by passing the --simplifications-preset argument to the command line interface, or by passing the simplifications argument to the Python API.
The available simplifications are:
teleportAction: Allows agents to instantly move to any location in the environment.openDoors: All doors in the environment are open by default.selfWateringFlowerPots: Automatically waters all flower pots in the environment.noElectricalAction: Disables electrical actions, making it easier for agents to learn tasks that do not require electrical actions.openContainers: All containers in the environment are open by default.
The --simplifications-preset argument can be set to easy to apply the following simplifications:
teleportActionopenDoorsselfWateringFlowerPotsnoElectricalAction(for non-connectivity tasks)
[!WARNING] The
easypreset differs from what is described in the paper (see Appendix B.5). TheopenContainersis not included in that preset and should manually be added if desired.
Baseline Agents
DRRN: https://github.com/cognitiveailab/drrn-scienceworld
KG-A2C: https://github.com/cognitiveailab/kga2c-scienceworld
CALM: https://github.com/cognitiveailab/calm-scienceworld
Behavior Cloning and Decision Transformer: https://github.com/cognitiveailab/t5-scienceworld
Developers
To compile the ScienceWorld JAR file, follow these steps:
Prerequisites
You will need to have Java 1.8+ SDK installed on your system (shipped with most linux distributions). E.g. on Ubuntu, you can install it with:
sudo apt-get install openjdk-21-jdk
Then, install sbt (Scala Build Tool) by running:
echo "deb https://repo.scala-sbt.org/scalasbt/debian all main" | sudo tee /etc/apt/sources.list.d/sbt.list
echo "deb https://repo.scala-sbt.org/scalasbt/debian /" | sudo tee /etc/apt/sources.list.d/sbt_old.list
curl -sL "https://keyserver.ubuntu.com/pks/lookup?op=get&search=0x2EE0EA64E40A89B84B2DF73499E82A75642AC823" | sudo tee /etc/apt/trusted.gpg.d/sbt.asc
sudo apt-get update
sudo apt-get install sbt
Building the JAR
Once you have sbt installed, you can compile the ScienceWorld JAR file by running:
./simulator/package.sh
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