Principles of protein processing for a self-organising associative memory

Omer Qadir*, Jerry Liu, Jon Timmis, Gianluca Tempesti, Andy Tyrrell

*Awdur cyfatebol y gwaith hwn

Allbwn ymchwil: Pennod mewn Llyfr/Adroddiad/Trafodion CynhadleddTrafodion Cynhadledd (Nid-Cyfnodolyn fathau)

8 Dyfyniadau(SciVal)

Crynodeb

The evolution of Artificial Intelligence has passed through many phases over the years, going from rigorous mathematical grounding to more intuitive bio-inspired approaches. Despite the abundance of AI algorithms and machine learning techniques, the state of the art still fails to capture the rich analytical properties of biological beings or their robustness. Most parallel hardware architectures tend to combine Von Neumann style processors to make a multi-processor environment and computation is based on Arithmetic and Logic Units (ALU). This paper introduces an alternate architecture that is inspired from the biological world, and is fundamentally different from traditional processing which uses arithmetic operations. The architecture proposed here is targeted towards robust artificial intelligence applications.

Iaith wreiddiolSaesneg
Teitl2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010
Dynodwyr Gwrthrych Digidol (DOIs)
StatwsCyhoeddwyd - 2010
Digwyddiad2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010 - Barcelona, Sbaen
Hyd: 18 Gorff 201023 Gorff 2010

Cyfres gyhoeddiadau

Enw2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010

Cynhadledd

Cynhadledd2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010
Gwlad/TiriogaethSbaen
DinasBarcelona
Cyfnod18 Gorff 201023 Gorff 2010

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