For nearly 50 years, AI researchers have improved their ability to simulate one aspect of how the brain works: experience-driven change in the connections between neurons to improve the organism’s -- or the computer program’s -- behavior. This mechanism now lies at the heart of modern AI technologies. However, 'synaptic plasticity' is but one of millions of adaptive mechanisms that evolved to help organisms grow and learn to grapple with their environments, and many of those mechanisms are not limited to brains. Intelligent problem-solving was already discovered by evolution around the time bacteria evolved to clump together, and is used widely by cells and tissues throughout the body. Imagine an Institute that helps biologists, neuroscientists, ecologists and psychologists work with computer scientists to turn hundreds of these adaptive mechanisms into code. Imagine further an AI that figures out how to combine these code pieces together to create AI programs, robots, and computer-designed organisms that inherit life’s breathtaking abilities to perform complex tasks, recover from unexpected situations, and work well with others. Organisms can do these things because they constantly adapt their brains, bodies, and coalesce into ever larger functional groups, like communities and societies. For this reason this project will use the next two years to lay the groundwork for the Proteus Institute, named after the Greek god of constant change. Along the way, the project will provide opportunities for students, policy makers, companies and the general public to influence how such technology is created.

Living systems continue to outstrip the most adaptive state-of-the-art artificial intelligence (AI) and robotics. One reason for this is that, without exception, organisms and species constantly restructure themselves at all organizational levels, from the microsecond- to millennial time scales; most machines do not. Almost all AI and robots incorporate change at just one time scale – that of synaptic plasticity – and in one modality: neural networks. This project will thus plan the Proteus Institute, dedicated to studying embodied plasticity: how multi-level change supports intelligence in protean systems (cells, organs, organisms, and ecologies), and how best to channel those discoveries into protean machines (robots and computer designed organisms) and algorithms (machine learning methods). To achieve this, the project will construct a continuously-running evolutionary algorithm that designs and trains robots and ML algorithms, using the insights of basal cognition and the multi-scale control systems of developmental biology. This algorithm will be increasingly enriched by software patches that simulate new and potentially useful adaptive mechanisms. This will enable the algorithm to discover combinations of domain agnostic adaptive mechanisms in a growing set of embodied AI and ML substrates. The project will also host two workshops where it will elicit candidate biological mechanisms not yet incorporated into robots or ML methods from biologists, neuroscientists, ecologists and psychologists. During the second workshop, the project will convene computational researchers to begin incorporating those mechanisms, and invite policy, industry, and other stakeholders to discuss how the emerging biology-to-AI pipeline could facilitate technology transfer, education, workforce development, and policy.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

National Science Foundation (NSF)
Division of Information and Intelligent Systems (IIS)
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Sridhar Raghavachari
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University of Vermont & State Agricultural College
United States
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