PswarmRadiusParallel function

Intern function, do not use yourself

Intern function, do not use yourself

Finds the weak Nash equilibirium of the data bots for one epoch depending on a radius, which requires the setting of constants, grid, and so on in, see Pswarm.

PswarmRadiusParallel(DataBotsPos, DataDists, AllallowedDBPosR0, IndPossibleDBPosRe, IndPossibleDBPosIm, Lines, Columns, Radius, NumAllDB, NumChoDB, NumFreeShape1, NumJumps, Origin1, Origin2, Happiness, MinIterations, HappinessInclination, Eps, debug)

Arguments

  • DataBotsPos: Numeric vector [1:NumJumpsn2] containing the current positions and all positions for considered/possible jumps which can be computed (depending on number of jumps parameter NumJumps) for the databots on two dimensions.
  • DataDists: Numeric vector with vectorized distance matrix of the datapoints in the original (high-dimensional) data space
  • AllallowedDBPosR0: NumericMatrix, see AllallowedDBPosR0 in setPolarGrid
  • IndPossibleDBPosRe: Numeric Vector of possible positions of the 1st coordinate.
  • IndPossibleDBPosIm: Numeric Vector of possible positions of the 2nd coordinate.
  • Lines: Integer stating the number of Lines the polar grid consists of.
  • Columns: Integer stating the number of columns the polar grid consists of.
  • Radius: Numeric (Integer) stating the moving radius of the databots
  • NumAllDB: Integer total number of databots
  • NumChoDB: Integer number of databots chosen for moving/jumps.
  • NumFreeShape1: Integer stating the first dimension of the numeric matrix book keeping the possible position grid
  • NumJumps: Integer number of jumps
  • Origin1: Numeric origin coordinate 1
  • Origin2: Numeric origin coordinate 2
  • Happiness: Numeric value indicating the global happiness over all databots
  • MinIterations: asdf
  • HappinessInclination: asdf
  • Eps: optional, double: Stop criterion for convergence of each epoche.
  • debug: optional, bool: If TRUE prints status every 100 iterations

Returns

list of - AllDataBotsPos: ComplexVector, indizes of DataBot Positions after a weak Nash equlibrium is found

  • stressverlauf: NumericVector, intern result, for debugging only

  • fokussiertlaufind: NumericVector, intern result, for debugging only

Details

Algorithm is described in [Thrun, 2018, p. 95, Listing 8.1].

References

[Thrun, 2018] Thrun, M. C.: Projection Based Clustering through Self-Organization and Swarm Intelligence, doctoral dissertation 2017, Springer, Heidelberg, ISBN: 978-3-658-20539-3, tools:::Rd_expr_doi("10.1007/978-3-658-20540-9") , 2018.

[Thrun/Ultsch, 2021] Thrun, M. C., and Ultsch, A.: Swarm Intelligence for Self-Organized Clustering, Artificial Intelligence, Vol. 290, pp. 103237, tools:::Rd_expr_doi("10.1016/j.artint.2020.103237") , 2021.

[Stier/Thrun, 2024] Stier, Q. and Thrun, M. C.: An efficient multicore CPU implementation of the DatabionicSwarm, 18th conference of the International Federation of Classification Societies (IFCS), San José, Costa Rica, July 14-19, 2024.

Author(s)

Quirin Stier

  • Maintainer: Michael Thrun
  • License: GPL-3
  • Last published: 2024-06-20