Principles of Protein Processing for a Self-Organising Associative Memory

TY - JOUR

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 - 2010/7

Y1 - 2010/7

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.

KW - NETWORK

KW - ARCHITECTURE

KW - MACHINE

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

M3 - Article

SP - 3836

EP - 3843

JO - 2010 ieee congress on evolutionary computation (cec)

JF - 2010 ieee congress on evolutionary computation (cec)

ER -