Computer Science

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28 Sep 2021

Loughborough to lead project aimed at enabling independent AI systems to learn from each other

A new international project seeks to create advanced AI programmes that will enable machines to learn progressively over a lifetime and share those experiences with each other.

Researchers hope the technology will allow machines to reuse information, adapt quickly to new conditions and collaborate by sharing information.

The project is part of the initiative Shared-Experience Lifelong Learning (ShELL), a program funded by the Defense Advanced Research Projects Agency (DARPA) – a US government agency credited for some of the biggest technological advances in recent history such as the Internet, the miniaturization of GPS, Siri and the computer mouse.

It started this month and is being led by Dr Andrea Soltoggio of Loughborough’s Computer Science department, in partnership with Dr Soheil Kolouri at Vanderbilt University and Dr Cong Liu at the University of Texas at Dallas, both in the USA.

Dr Soltoggio said: “The idea behind this project is to gain a deep understanding of how and what an AI system learns when dealing with a new task, so that we can exploit task similarities and share information to create fast, reliable and collaborating learning agents.

“One exciting aspect that goes beyond pure technological advances is that this research addresses high-level questions. How can individual entities share information and benefit from each other’s experiences when learning together?

“If one agent makes mistakes while learning a task, can this experience be shared with other agents so that they don’t make the same mistakes?

“Currently, these questions are mostly unanswered, but our proposal sets out lines of investigation to create such learning processes within AI agents.”

Each university involved in the project will build upon different aspects of lifelong learning, a relatively new area of machine learning research that has grown also with the contribution of the previous Lifelong Learning Machines (L2M) DARPA programme.

Loughborough will focus on novel bio-inspired neural networks that learn shareable knowledge exploiting neuromodulation and synaptic consolidation mechanisms.

Vanderbilt University will concentrate on the algorithmic theory and statistical foundation of the learning mechanisms, and Texas University will focus on the hardware integration and deployment for potential transition to industrial and real-world applications.

The real-world uses of this new technology could include co-operating self-learning autonomous vehicles such as self-driving cars, robotic rescue and exploration systems, distributed monitoring systems to detect emergencies, or cyber security systems of agents that monitor large networks.

The funding is part of DARPA’s Artificial Intelligence Exploration (AIE) program – a streamlined research and development scheme aimed at encouraging quick innovations in rapidly acceleration technology.

Professor Claudia Eberlein, Dean of Loughborough’s School of Science, said: “This funding from DARPA represents a phenomenal success for the University. It recognises the international standing of our AI experts and Dr Soltoggio’s position among the leading authorities in the world on AI.”