for(s in 1:nrow(kStates)){
  innerSum1 <- rep(0, m+1)
  innerSum2 <- rep(0, m+1)
  for(k in 1:m){#current state
    for(j in 1:m){#observed det lvl
      nextStateNr1 <- insp1StateNr[s,j]
      nextStateNr2 <- insp2StateNr[s,j]
      innerSum1[k] <- innerSum1[k] + obsProbsInsp1[k,j]*min(c2goDN[nextStateNr1], c2goPM[nextStateNr1])
      innerSum2[k] <- innerSum2[k] + obsProbsInsp2[k,j]*min(c2goDN[nextStateNr2], c2goPM[nextStateNr2])
    }
  }
  c2goInsp1[s] <- c_insp1 + sum(kStates[s,]*innerSum1)
  c2goInsp2[s] <- c_insp2 + sum(kStates[s,]*innerSum2)
}

#####################TEST ALTERNATIVE###############
optAfterInsp1 <- rep(NA, m)
optAfterInsp2 <- rep(NA, m)
innerSum1 <- rep(NA, m)
innerSum2 <- rep(NA, m)
for(s in 1:nrow(kStates)){
  for(j in 1:m){
    optAfterInsp1[j] <- min(c2goDN[insp1StateNr[s,j]], c2goPM[insp1StateNr[s,j]])
    optAfterInsp2[j] <- min(c2goDN[insp1StateNr[s,j]], c2goPM[insp1StateNr[s,j]])

    innerSum1[j] <- sum(kStates[s,]*obsProbsInsp1[,j])
    innerSum2[j] <- sum(kStates[s,]*obsProbsInsp2[,j])
  }
  c2goInsp1 <- c_insp1 + sum(optAfterInsp1*innerSum1)
  c2goInsp2 <- c_insp2 + sum(optAfterInsp2*innerSum2)
}