When intelligence is distributed across many parts, be they robots, devices, or objects, it can be tricky for the bigger picture to emerge. Yet answering these questions is key to making collective systems that are easy to design, monitor and control.

EMERGE will deliver a new philosophical, mathematical, and technological framework to demonstrate, both theoretically and experimentally, how a collaborative awareness – a representation of shared existence, environment and goals – can arise from the interactions of elemental artificial entities.

In this effort, we will rely only on unstructured conditions that the real world demands without leveraging a pre-existing shared language between them. Our goal is to surpass the limitations and barriers of the current state-of-the-art distributed systems to produce breakthroughs and open new markets in the next generation of robotic systems.

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Latest News

Workshop Awareness in Artificial Agents

Workshop Awareness in Artificial Agents

Calendar30 July 2025

EMERGE and VALAWAI projects invite you to the Biennale in Venice, Italy, on 6-8 September, to reflect on the nature of awareness through science, technology and art.

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Publication: Learning Low-Dimensional Strain Models of Soft Robots by Looking at the Evolution of Their Shape with Application to Model-Based Control

Publication: Learning Low-Dimensional Strain Models of Soft Robots by Looking at the Evolution of Their Shape with Application to Model-Based Control

Calendar04 June 2025

In this work, EMERGE partners from Delft University of Technology introduce a streamlined method for learning low-dimensional, physics-based models that are both accurate and easy to interpret.

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Publication: Nanowire Neural Networks for time-series processing

Publication: Nanowire Neural Networks for time-series processing

Calendar14 May 2025

In this work, EMERGE partners from the University of Pisa introduce a novel computational framework inspired by the physics of nanowire memristive networks, which they embed into the context of Recurrent Neural Networks (RNNs) for time-series processing.

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Partners

The EMERGE consortium brings together the University of Pisa (Italy), Ludwig Maximilian University of Munich (Germany), Delft University of Technology (Netherlands), University of Bristol (United Kingdom), and Da Vinci Labs (France).

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