fm.generate_fm_randomwalk {Rfmtool}

Function for generating several k-additive fuzzy measure

Description

Generates num k-additive fuzzy measures in the standard or Mobius representation using random walk of length markov of stepsize step.

Usage

  fm.generate_fm_randomwalk(num, n, kadd, markov, option, step, Fn, env)

Arguments

num

Generated num random fuzzy measures stored consecutively in standard or cardinality ordering in the array v.

n

Number of inputs

kadd

kadd is the value of k-additivity, which is used for reducing the complexity of fuzzy measures. default value is kadd = n. 1 < kadd < n+1; if kdd=n - f.m. is unrestricted. The parameter kadd only matters for options 3 and 5

markov

Number of Markov steps to take, the randomness increases with that number.

option

Option = 0 - normal, 1 convex (supermodular), 2 antibuoyant, 3 kadditive , 4 belief measure, 5 kadditive convex. The measure generated is in standard representation fo all options except 3,5. The parameter kadd only matters for options 3 and 5. In that case the measure is in more compact Mobius representation.

step

The maximum size of random steps (with respect to each value). The actual step is a random value up to Step.

Fn

The callback function to verify any additional conditions on generated FM. Provided by the user. if not NULL, is a callback function to perform additional check at every Markov step of the current set function, i.e., any extra conditions

env

Environment variable obtained from fm.Init(n).

Value

output

The output is named list with the first element v being the fuzzy measure and the second being the length of the array containing it

Author(s)

Gleb Beliakov, Andrei Kelarev, Quan Vu, Daniela L. Calderon, Deakin University

Examples

 
   Fn <- function(n,v){
        out <- 0.0

        for(i in 1:n) out<- out+v[i];
        
        if(out>1) {
        return(0)
        } else
        return(1)
    }
    env<-fm.Init(3)
    step <- 0.0010
    Option <- 3
    n <- 3

  fuzzymeasures <- fm.generate_fm_randomwalk(2, 3, 2, 1000, Option, step, Fn, env)
  print(fuzzymeasures)
  print(fuzzymeasures$length)