Principles of protein processing for a self-organising associative memory

Omer Qadir; Jerry Liu; Jon Timmis; Gianluca Tempesti; Andy Tyrrell

doi:10.1109/CEC.2010.5586419

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

Cyfrifiadureg

University of York

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

8 Dyfyniadau (Scopus)

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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 wreiddiol	Saesneg
Teitl	2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010
Dynodwyr Gwrthrych Digidol (DOIs)	https://doi.org/10.1109/CEC.2010.5586419
Statws	Cyhoeddwyd - 2010
Digwyddiad	2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010 - Barcelona, Sbaen Hyd: 18 Gorff 2010 → 23 Gorff 2010

Cyfres gyhoeddiadau

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

Cynhadledd

Cynhadledd	2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010
Gwlad/Tiriogaeth	Sbaen
Dinas	Barcelona
Cyfnod	18 Gorff 2010 → 23 Gorff 2010

Mynediad at Ddogfen

10.1109/CEC.2010.5586419

Cysylltiad parhaol

Dolen barhaus

Ffeiliau eraill a chysylltiadau

Dolen i’r cyhoeddiad yn Scopus

Dyfynnu hyn

Qadir, O., Liu, J., Timmis, J., Tempesti, G., & Tyrrell, A. (2010). Principles of protein processing for a self-organising associative memory. Yn 2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010 erthygl 5586419 (2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010). https://doi.org/10.1109/CEC.2010.5586419

Qadir, Omer ; Liu, Jerry ; Timmis, Jon et al. / Principles of protein processing for a self-organising associative memory. 2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010. 2010. (2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010).

@inproceedings{4b94de083f9a4e7392776544d318ae74,

title = "Principles of protein processing for a self-organising associative memory",

abstract = "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.",

author = "Omer Qadir and Jerry Liu and Jon Timmis and Gianluca Tempesti and Andy Tyrrell",

year = "2010",

doi = "10.1109/CEC.2010.5586419",

language = "English",

isbn = "9781424469109",

series = "2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010",

booktitle = "2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010",

note = "2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010 ; Conference date: 18-07-2010 Through 23-07-2010",

}

Qadir, O, Liu, J, Timmis, J, Tempesti, G & Tyrrell, A 2010, Principles of protein processing for a self-organising associative memory. yn 2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010., 5586419, 2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010, 2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010, Barcelona, Sbaen, 18 Gorff 2010. https://doi.org/10.1109/CEC.2010.5586419

Principles of protein processing for a self-organising associative memory. / Qadir, Omer; Liu, Jerry; Timmis, Jon et al.
2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010. 2010. 5586419 (2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010).

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

TY - GEN

T1 - Principles of protein processing for a self-organising associative memory

AU - Qadir, Omer

AU - Liu, Jerry

AU - Timmis, Jon

AU - Tempesti, Gianluca

AU - Tyrrell, Andy

PY - 2010

Y1 - 2010

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=79959487619&partnerID=8YFLogxK

U2 - 10.1109/CEC.2010.5586419

DO - 10.1109/CEC.2010.5586419

M3 - Conference Proceeding (Non-Journal item)

AN - SCOPUS:79959487619

SN - 9781424469109

T3 - 2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010

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

T2 - 2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010

Y2 - 18 July 2010 through 23 July 2010

ER -

Qadir O, Liu J, Timmis J, Tempesti G, Tyrrell A. Principles of protein processing for a self-organising associative memory. Yn 2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010. 2010. 5586419. (2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010). doi: 10.1109/CEC.2010.5586419

Principles of protein processing for a self-organising associative memory

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