Active InferAnts is a multiagent modeling project that applies Active Inference to collective behavior, inspired by ant colony dynamics. It has produced a GitHub repository, a 2021 paper, and code developed within the Active Blockference project, with multiple realizations across different modeling contexts.
Overview
Active InferAnts develops multiagent models using Active Inference to simulate and understand collective behavior. The project draws inspiration from social insect biology — particularly ant colony foraging and organization — and applies generative modeling to understand how local agent behaviors produce collective intelligence without central coordination.
Past Work and Papers
The project has a 2021 paper, a GitHub repository with multiple code realizations, and is developed in part through the Active Blockference project. The work spans individual agent models, collective foraging scenarios, and theoretical extensions.
Participate
Contributors with backgrounds in computational biology, multiagent systems, Active Inference, or behavioral ecology are welcome. Technical contributions (code, models) and conceptual work (theory, documentation) are both valued.