A Julia implementation of the card game Joker Jail Break
Author itsdfish
2 Stars
Updated Last
1 Year Ago
Started In
December 2022


The purpose of this package is to simulate and play the game Joker Jail Break. Basic documentation for using the package is provided below.


Joker jail break is a simple card matching game developed by Ramon Huiskamp. The goal is to remove the Joker from the jail cell. As shown below, the Joker is placed the center of a 3 X 3 matrix of card piles which serves as a jail cell. The corners have 3 cards and the other piles have 7 cards. The Joker can breakout once either the top, bottom, left or right pile is depleted. Joker cannot escape from the corners, but cards in those piles can be used strategically.

Cards are removed by selecting cards such that the sum of the black and sum of the red cards are equal. In some situations, a valid card selection does not exist. A card from the remaining deck can be placed on the Joker in an attempt to resolve the impasse. However, cards placed on the Joker must ultimately be removed, and a maximum of three cards can be placed on the Joker at any time. The game ends when Joker is free, or no moves are possible. An online version of Joker jail break can be found here: (


At minimum, the API requires one to define a subtype of AbstractPlayer, and a corresponding decide function. Here is an outline of a player:

struct Player <: AbstractPlayer
    # optional fields

Note that fields can be added as needed. The following code block shows the outline of the decide method, which returns two variables: stop which indicates whether the player stops the game, and indices which are the indices of the selected cards.

function decide(player::Player, board, card_counts, deck_size; kwargs...)
    # intentionally blank
    return stop,indices

After defining the player subtype and decide function, the game can be simulated by creating an instance of a game, the player, and passing them to simulate!. A minimal example is provided in the following section.

Three other methods in API can be optionally defined. setup allows you to configure the player before starting the game.

function setup!(player::Player, board, card_counts; kwargs...)
    # intentionally blank
    return nothing

By default, only the number of rounds and the outcome of the game are collected. However, JokerJailBreak.jl provides two methods for custom data collection during the simulation: update_data_round, which is called after each round, and update_data_end which is called after the game has finished. To define custom data collection, first define a custom data type (e.g., MyData), and define the methods below:

function update_data_round!(game, player, data::MyData, stop; kwargs...)

    return nothing
function update_data_end!(game, player, data:MyData, stop; kwargs...)

    return nothing


The following example illustrates how to develop a simple player. The first step is to use the required libraries.

using JokerJailBreak
import JokerJailBreak: AbstractPlayer, decide
using StatsBase
using Random

Next, we will make a subtype of AbstractPlayer called Player so that we can extend the decide function. In practice, fields can be added to a subtype of AbstractPlayer, but it is not necessary for this example.

struct Player <: AbstractPlayer


Now that we have defined our own subtype of AbstractPlayer, we can define the player's decision logic. The player will select random pairs of cards until a match is found (e.g., 5 black, 5 red), or 1000 attemps have been made. If no matches are found, the player stops the game. The function decide will return two variables: stop which indicates whether the player stops the game, and indices which are the indices of the selected cards. The function sample from the package StatsBase will be used to sample pairs of card indices without replacement.

function decide(player::Player, board, card_counts, deck_size)
    indices = Int[]
    cnt = 0
    while cnt < 1000 
        cnt += 1
        indices = sample(1:9, 2, replace=false)
        any(i -> board[i] == nothing, indices) ? continue : nothing
        is_zero_sum(board, indices) ? break : nothing
    stop = cnt < 1000 ? false : true 
    cnt == 1000 ? empty!(indices) : nothing
    return stop,indices

The last steop is to simulate the game with simulate!. The default data object with a round count and outcome indicator (win, not_winnable) will be returned if a custom data type is not passed.

game = Game()
player = Player()
simulate!(game, player)

One question you might want to answer is how often does this strategy solve the game? Let's wrap the code block above in a function.

function wrapper(;kwargs...)
    game = Game()
    player = Player()
    return simulate!(game, player; kwargs...)

Now, let's set the seed of the random number generator and repeat the simulation 1,000 times.

data = map(x -> wrapper(), 1:1000)
mean(x -> x.outcome == :win, data)

As expected, the win probability is low: 0.002.

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