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Memetic-Computing

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Memetic Computing is a novel computational paradigm that incorporates the notion of meme(s)[1] as basic units of transferable information encoded in computational representations for boosting the performance of artificial evolutionary systems in the domain of search and optimization.[2][3][4]

The term memetic computing is often unassumingly misinterpreted to mean the same thing as memetic algorithms[5] that typically hybridize population-based global search algorithms with one or more local search schemes. Notably, memetic computing offers a much more broader scope, perpetuating the idea of memes into concepts that pave way towards simultaneous problem learning and optimization approach.


Methods

There are two different methods that describe the history and rise of memetics in computing. These are Human crafted memes and Machine crafted memes.

Human Crafted Memes

1st generation MA ls+global

little explicit provision for learning relevant knowledge (8)

automation integrations of human crafted ls heuristics (vi) Successor to predefined searches- muoti heuritics meta larmakian evolved as

Machine crafting Memes

A stepping stone.. concept of memes set free the narrow scope (iv) - fully automated knowledge dispersal and exploitation.

Applications

The concept of memes have been exploited in various research fields, for example, robotics engineering, multi-agent systems, robotics, optimization[6], software engineering, and the social sciences etc.

See also

References

  1. ^ Dawkins, R. (1976). The selfish gene. Oxford University Press.
  2. ^ Ong, Y. S., Lim, M. H., & Chen, X. (2010). Memetic computation—past, present & future [research frontier]. IEEE Computational Intelligence Magazine, 5(2), 24-31.
  3. ^ Chen, X., Ong, Y. S., Lim, M. H., & Tan, K. C. (2011). A multi-facet survey on memetic computation. IEEE Transactions on Evolutionary Computation, 15(5), 591-607.
  4. ^ Gupta, A., & Ong, Y. S. (2018). Memetic Computation: The Mainspring of Knowledge Transfer in a Data-Driven Optimization Era (Vol. 21). Springer.
  5. ^ Moscato, P. (1989). On evolution, search, optimization, genetic algorithms and martial arts: Towards memetic algorithms. Caltech concurrent computation program, C3P Report, 826, 1989.
  6. ^ Feng, L., Ong, Y. S., Lim, M. H., & Tsang, I. W. (2015). Memetic search with interdomain learning: A realization between CVRP and CARP. IEEE Transactions on Evolutionary Computation, 19(5), 644-658.