| EPSRC Reference: |
EP/X018733/1 |
| Title: |
Autonomous Learning and Development in Embodied Neuromorphic Systems (ALDENS) |
| Principal Investigator: |
Di Nuovo, Professor A |
| Other Investigators: |
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| Department: |
College of Business, Technology & Eng |
| Organisation: |
Sheffield Hallam University |
| Scheme: |
Standard Research - NR1 |
| Starts: |
30 January 2023 |
Ends: |
29 January 2025 |
Value (£): |
202,144
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| No relevance to Underpinning Sectors |
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Summary on Grant Application Form |
This project ambition is to create an open-ended artificial mind for robots that can grow up like a child - autonomously learning and developing new skills via multimodal interaction with humans and the environment. This will enable a globally desired paradigm shift in AI and robotics: from performing narrowly pre-defined tasks to autonomous mental development.
To this end, ALDENS will pioneer an innovative cross-disciplinary approach to generate models of interactive robots with real-time developmental human-like learning made possible by efficient brain-like (neuromorphic) computing, which will go above and beyond what is currently possible with the mainstream deep-learning approach.
The ALDENS project will establish the new developmental neuromorphic paradigm, a synergic combination that will go beyond the limitations of the individual paradigms: developmental robotics will deliver the missing learning mechanisms for neuromorphic spiking neural networks; meanwhile, neuromorphic computing will provide efficient brain-like resources with an accurate representation of the real world.
Specifically, the research in this project will create and validate new ground-breaking methodologies to build an autonomous, flexible, and scalable artificial brain architecture. These will transform the design of interactive robots' cognitive architectures. Indeed, the planned innovative developments will pave the way for the expected paradigm shift and lay the foundations of the next generation of truly autonomous robots able to reason, behave and interact in a human-like fashion.
A general risk factor for research modelling of the human brain is that its functional organisation and learning mechanisms are not yet fully understood. There is disagreement within the cross-disciplinary scientific community regarding the fundamental structure and capabilities that should be modelled in artificial agents. This makes this research uncertain, with each discipline having its own view of "intelligence"; different experimental procedures and methodologies to interpret the results.
Importantly, the new developmental neuromorphic models will be a powerful tool for increasing the research capacity in life sciences, like developmental psychology and neuroscience. Researchers will be able to use the developmental neuromorphic models to gain information and progress our understanding of human learning and intelligence. Biologically plausible simulations envisioned by this project will allow researchers to quickly collect information in support of novel experimental predictions before being tested on humans. Interestingly, it will be possible to lesion models to replicate cognitive dysfunctions to generate simulated information of the inner workings of the brain that cannot be discovered otherwise. This method would be useful for boosting the understanding of neurodevelopmental and learning disorders for the enhancement of their diagnosis and treatment.
Ethical issues, lack of trust and prejudice of the public can result in the rejection of self-learning robots and negate the future socio-economic impact of this research.
The envisioned humanization of the learning process will positively impact people's trust, acceptance, and adoption of robots in people lives. The new methodologies will enable intelligent robots to learn like humans, a new capability that will boost social applications by achieving the highest degree of personalisation, i.e. the needs and preferences of the teacher (user) can shape the artificial minds, making the interaction more natural and acceptable.
To maximise the future social and economic impact, the ALDENS project will also regularly engage stakeholders in AI ethics and the public to receive discuss the research and get feedback on the definition of the ethical and legal boundaries for trust, safety, and wider acceptance.
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Key Findings |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Potential use in non-academic contexts |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Impacts |
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| Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
| Summary |
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| Date Materialised |
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Sectors submitted by the Researcher |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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| Project URL: |
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| Further Information: |
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| Organisation Website: |
http://www.shu.ac.uk |