How to plot a 2D reinforced random walk with ggplot?

[Kevser_Cifci]

Hello!
Is there a way to plot a 2D reinforced random walk with different values for alpha?

Next_step = function(i,j,Grille){
  
  l = nrow(Grille)
  prob = rep(NA,4)
  
  prob[1] = Grille[i+1,j]/(Grille[i,j-1]+Grille[i,j+1]+Grille[i-1,j]+Grille[i+1,j])
  prob[2] = Grille[i,j+1]/(Grille[i,j-1]+Grille[i,j+1]+Grille[i-1,j]+Grille[i+1,j])
  prob[3] = Grille[i,j-1]/(Grille[i,j-1]+Grille[i,j+1]+Grille[i-1,j]+Grille[i+1,j])
  prob[4] = Grille[i-1,j]/(Grille[i,j-1]+Grille[i,j+1]+Grille[i-1,j]+Grille[i+1,j])
  next_step = sample(1:4, 1,replace = TRUE, prob = prob)
  
  
  if (next_step == 1) { # en bas
    i = i+1
  } else if (next_step == 2) {  # à droite 
    j = j+1
  } else if (next_step == 3) { # à gauche
    j= j-1
  } else if (next_step == 4) { # en haut 
    i = i-1
  }
  return(c(i,j))
}
RW_2d_start = function(n,pas, alpha){
  
  Grille = matrix(1, nrow = n+2, ncol = n+2)
  Grille[c(1,n+2),] = 0
  Grille[,c(1,n+2)]=0
  
  axe_x = rep(NA,pas)
  axe_y = rep(NA,pas)
  d = rep(NA,2)
  
  if (n%%2 != 0) {axe_x[1] = floor(n/2)} else {axe_x[1] = n/2} ## on commence du milieu
  axe_y[1] = axe_x[1]
  Grille[axe_x[1],axe_y[1]] = Grille[axe_x[1],axe_y[1]]+alpha
  for (i in 2:pas){ 
    d[1:2]= Next_step(axe_x[i-1],axe_y[i-1],Grille) 
    axe_x[i]=d[1] 
    axe_y[i]=d[2] 
    Grille[d[1],d[2]] = Grille[d[1],d[2]]+alpha
  }
  return(list(path = data.frame(step = seq_along(axe_x), x = axe_x, y = axe_y),
              Grille = Grille))
}
r <- RW_2d_start(100,10000,0)
r_path <- r$path
ggplot(r_path) +
  theme_classic() +
  geom_path(aes(x = x, y = y, color = step)) +
  scale_color_steps(low = "blue",
                    high = "red") +
  labs(
    title    = "alpha = 0",
    x        = "position x",
    y        = "position y")

I want to plot RW_2d_start function with different values of alpha and the number of steps in the same graph.
Is this possible?

Thank you!