README.md

MARIOAI

This repository is a python focused base for the Mario AI tool. All original code can be found in:

http://julian.togelius.com/mariocompetition2009/

Server configuration

Note: you need java installed and configured in your computer in order to run the server.

Whether execute the server.bat or use the following command inside the server directory:

java ch.idsia.scenarios.MainRun -server on

Marking a python bot

The original code provided by Togelius were simplified and can be found in marioai package. Now, you can simply inherit the marioai.Agent class and implement its methods. Use the following boilerplate:

class MyAgent(marioai.Agent):
    def sense(self, obs):
        super(MyAgent, self).sense(obs)

    def act(self):
        return [0, 0, 0, 0, 0]

    def giveRewards(self, reward, cum_reward):
        pass

Sensorial information

By default, the base agent store the following sensorial information:

• can_jump: a boolean attribute that tells if the agent can jump or not.
• on_ground: tells if the agents is touching the ground or not.
• mario_floats: the Mario position on the level.
• enemies_floats: the enemies position on the level.
• level_scene: a 22x22 numpy array containing the elements of the level aroung the agent (Mario is at [11, 11]).

Value	Meaning
-11	soft obstacle, can jump through
-10	hard obstacle, cannot pass through
0	no obstacle or enemy
1	mario
2	Enemy goomba
3	Enemy goomba winged
4	Enemy red koopa
5	Enemy red koopa winged
6	Enemy green koopa
7	Enemy green koopa winged
8	Enemy bullet bill
9	Enemy spiky
10	Enemy spiky winged
12	Enemy flower
13	Enemy shell
14	mushroom
15	fire_flower
16	brick (simple/with coin/with mushroom/with flower)
20	enemy obstacle (ex.: flower pot or parts of a cannon)
21	question brick (with a coin or mushroom/flower)
25	mario weapon projectile
42	undefined

Control signals

Each position of the array represents a different action, use 1 to enable an action and 0 to disable it:

[backward, forward, crouch, jump, speed/bombs]

Example:

# send the agent to the right
def act(self):
    return [0, 1, 0, 0, 0]

# jump backward
def act(self):
    return [1, 0, 0, 1, 0]