Diffusive Habitats is an autonomous adaptable system that builds upon the juncture of distributed robotics, artificial intelligence, and digital platforms, to reimagine the way we conceive and inhabit architecture. Addressing the ecological crisis, the project contrasts the unsustainable linear life-cycles of traditional construction with a model inspired by the efficiency and adaptability of natural systems.

Diffusive Habitats enables users to access an online platform and, in collaboration with bespoke AI-enhanced algorithms, collectively situate, design, and kick-start a new habitat. Subsequently, their spaces are constructed by a swarm of custom collaborative robots driven by multi-agent intelligence. And, thereafter, under a distributed ownership model fostering collaboration, communities trigger further spatial, programmatic, and formal adjustments on-demand. This flexibility enables, for instance, ad-hoc working spaces, seasonal environmental adaptations, dynamic adjustments for cultural celebrations, and beyond, generating a living environment capable of self-assessment, organization, and improvement.

Diffusive Habitats’ reconfiguration system is composed of three interrelated components: a sophisticated platform for participative space-planning, a physical robotic material system, and an additive framework for robotic intelligence featuring deep reinforcement learning. Each of the components’ shapes, materials, fabrication processes, and functions were developed in conjunction via rigorous cycles of AI-assisted design, digital fabrication, and physical experimentation. Ultimately, the complete system was successfully tested in large-scale cyber-physical transformations and deployed for an architectural case-study located in Herme Hill Road, Brixton, London.

In 2023, the project's unique transdisciplinary contributions were recognized by Association for Computer Aided Design in Architecture in the 2023 ACADIA Conference, where Diffusive Habitats presented two research papers on autonomous collaborative robotic reconfiguration with deep multi-agent reinforcement learning. Now, the project is committed to continue providing sustainable alternatives for traditional construction, deploying groundbreaking models for enhanced human inhabitation, and raising awareness about the untapped potential of the integration of AI and technological innovation in architecture.