Neurosymbolic Spike Concept Learner towards Neuromorphic General Intelligence

Wahab, Ahmad and Mahbub, Khaled and Tawil, Abdel-Rahman H. (2021) Neurosymbolic Spike Concept Learner towards Neuromorphic General Intelligence. In: 13th International Conference on Agents and Artificial Intelligence, 4th - 6th February 2021.

ICAART_2021_229_CR.pdf - Accepted Version

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Current research in the area of concept learning makes use of deep learning and ensembles methods to learn concepts. Concept learning allows us to combine heterogeneous entities in data which could collectively identify as individual concepts. Heterogeneity and compositionality are crucial areas to explore in machine learning as it has the potential to contribute profoundly to artificial general intelligence. We investigate the use of spiking neural networks for concept learning. Spiking neurones inclusively model the temporal properties as observed in biological neurones. A benefit of spike-based neurones allows for localised learning rules that only adapts connections between relevant neurones. In this position paper, we propose a technique allowing dynamic formation of synapse (connections) in spiking neural networks, the basis of structural plasticity. Achieving dynamic formation of synapse allows for a unique approach to concept learning with a malleable neural structure. We call this technique Neurosymbolic Spike-Concept Learner (NS-SCL). The limitations of NS-SCL can be overcome with the neuromorphic computing paradigm. Furthermore, introducing NS-SCL as a technique on neuromorphic platforms should motivate a new direction of research towards Neuromorphic General Intelligence (NGI), a term we define to some extent.

Item Type: Conference or Workshop Item (Paper)
Additional Information: ** From Crossref proceedings articles via Jisc Publications Router
Identification Number:
4 December 2020Accepted
1 February 2021Published
Uncontrolled Keywords: Neuromorphic General Intelligence, Spiking Neural Networks, Functional Plasticity, Structural Plasticity, Neurosymbolic, Representation Learning, Concept Learning.
Subjects: CAH11 - computing > CAH11-01 - computing > CAH11-01-01 - computer science
Divisions: Faculty of Computing, Engineering and the Built Environment > School of Computing and Digital Technology
SWORD Depositor: JISC PubRouter
Depositing User: JISC PubRouter
Date Deposited: 22 Feb 2021 11:07
Last Modified: 12 Jan 2022 12:53

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