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Erschienen in:
2012 | OriginalPaper | Buchkapitel
Towards a Biomolecular Learning Machine
verfasst von : Matthew R. Lakin, Amanda Minnich, Terran Lane, Darko Stefanovic
Erschienen in: Unconventional Computation and Natural Computation
Verlag: Springer Berlin Heidelberg
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Learning and generalisation are fundamental behavioural traits of intelligent life. We present a synthetic biochemical circuit which can exhibit non-trivial learning and generalisation behaviours, which is a first step towards demonstrating that these behaviours may be realised at the molecular level. The aim of our system is to learn positive real-valued weights for a real-valued linear function of positive inputs. Mathematically, this can be viewed as solving a non-negative least-squares regression problem. Our design is based on deoxyribozymes, which are catalytic DNA strands. We present simulation results which demonstrate that the system can converge towards a desired set of weights after a number of training instances are provided.