Forager is a video game app commissioned by Uchida Lab Center for Brain Science at Harvard University to study human foraging behavior, mirroring mouse experiments. The app includes a front-end foraging game and a back-end admin panel for researchers to configure experiments and analyze gameplay data. The goal is to motivate human participants with engaging gameplay to gather reliable behavioral data. The game features simple mechanics, an instructions screen, and a leaderboard, while the admin panel allows for custom map creation, patch type configuration, and data visualization.

Play the game here.

Game design

 Handcrafted pixel art

Web game client

Custom scenarios API

Back-end administration panel

Database schema design & management

Security & data validation

Uchida Lab partnered with Good Animal to develop a simple foraging video game for collecting human behavioral data comparable to that gathered from mice. The project's core is an admin panel designed to configure and deploy various game levels, mirroring mouse experiments or testing specific hypotheses. Good Animal embraced the challenge, given the clearly defined vision and constraints on gameplay complexity. The resulting project consists of a front-end game and a back-end admin panel capable of configuring multiple game scenarios to test foraging behavior hypotheses using mechanics modeled after Uchida Lab's mouse experiments.

Forager was designed with simple, satisfying gameplay because fun is the best motivator for high scores. This differs significantly from motivating mice to find water.  We focused on creating a smooth and engaging foraging experience since extra features complicate data interpretation and we couldn't add mechanics due to the experiment's requirements.

The game starts with a concise instructions screen that introduces key information and controls.  As you forage, you’ll notice patterns and devise strategies to maximize points. At the end, a leaderboard enhances the social, gaming, and competitive aspects.

The admin panel allows researchers to create custom scenarios with pixel art patches and reward tracks. Experiments can be configured and shared individually to test multiple hypotheses at once. Researches can download session data to analyze player movement as they would mouse behavior.