schelling segregation model in shiny

Question

I tried to run the Schelling segregation model in shiny. I got 3 inputes: number of houses, number of neighbors and alike_preference and sorting should be done within 1000 seconds. The problem is I don't get the output. Also, I put my renderTable() function both in the eventreactive() and loop, and outside them , but still no output was shown.

library(shiny)
# UI
ui <- fluidPage(
  titlePanel("Schelling’s model!"),
  sidebarLayout(
    sidebarPanel( 
      sliderInput(inputId = "Ic1",
                  label = "Number of Houses:",
                  min = 1,
                  max = 51,
                  value =1),
      sliderInput(inputId = "Ic2",
                  label = "Number of Neighbours",
                  min=0,
                  max=2000,
                  step=50,
                  value = 0),
      sliderInput(inputId = 'Ic3',
                  label = 'alike_preference',
                  min=0,
                  max=1,
                  value=0),
      br(),
      actionButton(inputId = 'Id8','go',
                   style="color: #fff; background-color: #428fd6; border-color: #2e6da4")
     ),
    # Main panel for displaying outputs ----
    mainPanel(
      tableOutput(outputId = "map"),
    )
  )
)

#Now The cycle of changing places in 1000 seconds

server <- function(input, output) {
  grid_activation1 <- reactiveVal()
  grid_activation1 <- eventReactive(input$Id8 ,{
    input$Ic3
    group<-c(rep(0,(input$Ic1*input$Ic1)-input$Ic2,rep(1,input$Ic2/2),rep(2,input$Ic2/2)))
    grid <- matrix(sample(group,input$Ic1*Input$Ic1,replace=F), ncol= input$Ic1)
    image(grid,col=c("black","red","green"),axes=F)
    
    get_neighbors<-function(coords) { 
      n<-c()
      for (i in c(1:8)) {
        if (i == 1) {
          x<-coords[1] + 1
          y<-coords[2]
        }
        
        if (i == 2) {
          x<-coords[1] + 1
          y<-coords[2] + 1
        }
        
        if (i == 3) {
          x<-coords[1]
          y<-coords[2] + 1
        }
        
        if (i == 4) {
          x<-coords[1] - 1
          y<-coords[2] + 1
        }
        
        if (i == 5) {
          x<-coords[1] - 1
          y<-coords[2]
        }
        
        if (i == 6) {
          x<-coords[1] - 1
          y<-coords[2] - 1
        }
        
        if (i == 7) {
          x<-coords[1]
          y<-coords[2] - 1
        }
        
        if (i == 8) {
          x<-coords[1] + 1
          y<-coords[2] - 1
        }
        
        if (x < 1) {
          x<-51
        }
        if (x > 51) {
          x<-1
        }
        if (y < 1) {
          y<-51
        }
        if (y > 51) {
          y<-1
        }
        n<-rbind(n,c(x,y))
      }
      n
    }
    
    for (t in c(1:1000)) {
      happy_cells<-c()
      unhappy_cells<-c()  
      
      
      
      for (j in c(1:input$Ic1)) {
        for (k in c(1:input$Ic1)) {
          current<-c(j,k)
          value<-grid[j,k] 
          if (value > 0) {
            like_neighbors<-0
            all_neighbors<-0
            neighbors<-get_neighbors(current)
            for (i in c(1:nrow(neighbors))){
              x<-neighbors[i,1]
              y<-neighbors[i,2]
              if (grid[x,y] > 0) {
                all_neighbors<-all_neighbors + 1
              }
              if (grid[x,y] == value) {
                like_neighbors<-like_neighbors + 1
              }
            }
            if (is.nan(like_neighbors / all_neighbors)==FALSE) {
              if ((like_neighbors / all_neighbors) < input$Ic3) {
                unhappy_cells<-rbind(unhappy_cells,c(current[1],current[2]))
              }
              else {
                happy_cells<-rbind(happy_cells,c(current[1],current[2]))
              }
            }
            
            else {
              happy_cells<-rbind(happy_cells,c(current[1],current[2]))
            }
          }
        }
      }
      
      happiness_tracker<-append(happiness_tracker,length(happy_cells)/(length(happy_cells) + length(unhappy_cells)))
      rand<-sample(nrow(unhappy_cells))
      for (i in rand) {
        mover<-unhappy_cells[i,]
        mover_val<-grid[mover[1],mover[2]]
        move_to<-c(sample(1:input$Ic1,1),sample(1:input$Ic1,1))
        move_to_val<-grid[move_to[1],move_to[2]]
        while (move_to_val > 0 ){
          move_to<-c(sample(1:input$Ic1,1),sample(1:input$Ic1,1))
          move_to_val<-grid[move_to[1],move_to[2]]
        }
        grid[mover[1],mover[2]]<-0
        grid[move_to[1],move_to[2]]<-mover_val
      }
      
      image(grid,col=c("black","red","green"),axes=F)
      
     # I put output plotting in for loop to see changes Continuously

      output$map <- renderTable({
        grid_activation1
      }) 
    } 
  })
}

shinyApp(ui = ui, server = server)