Generating "Non-Random" Numbers in R?

I know how to generate 100 random numbers in R (without replacement):

random_numbers = sample.int(100, 100, replace = FALSE)

I was now curious about learning how to generate 100 "non random" numbers (without replacement). The first comes to mind is to generate a random number, and the next number will be the old number + 1 with a probability of 0.5 or an actual random number with probability 0.5. Thus, these numbers are not "fully random".

This was my attempt to write this code for numbers in a range of 0 to 100 (suppose I want to repeat this procedure 100 times):

library(dplyr)

all_games <- vector("list", 100) 

for (i in 1:100){

index_i = i
guess_sets <- 1:100 
prob_i = runif(n=1, min=1e-12, max=.9999999999)
    guess_i  = ifelse(prob_i> 0.5, sample.int(1, 100, replace = FALSE), guess_i + 1)
    guess_sets_i <- setdiff(guess_sets_i, guess_i)
all_games_i = as.list(index_i, guess_i, all_games_i)
all_games[[i]] <- all_games_i
}

all_games <- do.call("rbind", all_games)

I tried to make a list that stores all guesses such that the range for the next guess automatically excludes numbers that have already been guessed, but I get this error:

Error in sample.int(1, 100, replace = FALSE) : 
  cannot take a sample larger than the population when 'replace = FALSE'

Ideally, I am trying to get the following results (format doesn't matter):

index_1 : 5,6,51,4,3,88,87,9 ...
index_2 77,78,79,2,65,3,1,99,100,4...
etc.

• Can someone please show me how to do this? Are there easier ways in R to generate "non-random numbers"?

Thank you!

Note: I think an extra line of logic needs to be added - Suppose I guess the number 100, after guessing the number 100 I must guess a new random number since 100+1 is not included in the original range. Also, if I guess the number 5, 17 then 4 - and after guessing 4, the loop tells me to guess 4+1, this is impossible because 5 has already been guessed. In such a case, I would also have to guess a new random number?