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Reinforcement Learning v. Mario Kart Wii

presentation

Requirements

  • gym
  • numpy
  • OpenGL for vis
  • Pangolin for vis: Pangolin
  • Dolphin >= 5.0 Dolphin Emulator (my fork required for hotkey automation)

OpenAI Gym Environment

Usage

Environment Variables:

  • Set DOLPHIN_CONF_DIR to the Dolphin Emulator User directory (MacOS : ~/Library/Application Support/Dolphin)
  • Set DOLPHIN_DIR to the location of the Dolphin Binary (ex: dolphin/build/Binaries/Dolphin.app/Contents/MacOS/Dolphin)
  • Set MK_ISO to the location of the game iso

In-Progress:

  • CENTER_TRAJ 3D trajectory for driving on the centerline (centerline_traj.npy)
  • LEFT_TRAJ 3D trajectory for driving on the left side of the track (lefttraj.npy)
  • RIGHT_TRAJ 3D trajectory for driving on the right side of the track (righttraj.npy)
python3 -m pip install -e mario-env
import gym
import mario_env

env_id = "MarioEnv-v0"

env = gym.make(env_id)
env.reset()

Structure

  • mario-env
    • mario_env
      • envs
        • marioenv.py
          • Main Gym environment
        • memory_watcher.py
          • Blocking memory watching script to monitor memory changes from Dolphin Emulator.
        • trajectory.py
          • Helper class to store trajectory information (x, y, z) from memory updates
        • state.py
          • Helper class to store enums for state inforation and State objects to store state information
        • threaded_memory_watcher.py
          • Threaded memory watching script (replaces memory_watcher.py and state_manager.py)
        • state_manager.py
          • Script to accept memory updates and parse them into proper numerical state information
        • pangolin_handler.py
          • Houses threaded Visualizer object to update a 3D plot of current trajectory and others. Requires Pangolin
        • pad.py
          • Houses logic to send controller commands and hotkeys to Dolphin Emulator
        • constants.py
          • Configuration options
  • dolphin_configs
    • Dolphin.ini -> $DOLPHIN_CONF_DIR/Config/
    • GCPadNew.ini -> $DOLPHIN_CONF_DIR/Config/
    • Hotkeys.ini -> $DOLPHIN_CONF_DIR/Config/
    • Profiles/* -> $DOLPHIN_CONF_DIR/Config/

Monitored RAM Locations

PAL Version of MKwii

Address Offset Description
0x809C18F8 0x2B Stage Data (0: intro-camera, 1: race-countdown, 2: racing)
0x809BD70C 0x61 Moving Direction (1: forward, 2: backward)
0x809BD70C 0x3C Steering Direction (0: left, 7: straight, 14: right)
0x809BD70C 0x63 Use Item (0: No, 1: Yes)
0x809BD70C 0x4B DPad (8: Up, 16: Down, 32: Left, 64: Right)
0x809BD730 0x111 Current Lap (int)
0x809BD730 0x112 Maximum Lap (int)
0x809BD730 0xFC Max Lap Completion (float 1.5 -> halfway through first lap etc.)
0x809BD730 0xF8 Current Lap Completion (float 1.5 -> halfway through first lap etc.)
0x809C2EF8 0x40 + 0x0 X Position (float)
0x809C2EF8 0x40 + 0x4 Y Position (float)
0x809C2EF8 0x40 + 0x8 Z Position (float)
0x809C2EF8 0x40 - 0x160 Previous X Position (float)
0x809C2EF8 0x40 - 0x160 + 0x4 Previous Y Position (float)
0x809C2EF8 0x40 - 0x160 + 0x8 Previous Z Position (float)
0x809BD730 0x1B9 Minutes
0x809BD730 0x1BA Seconds
0x809BD730 0x1BC Third-Seconds

MarioKart Wii Symbol Map

TODO

  • Use trajectories of edges of the road to determine if kart is on the track or not
    • It seems that the x, z coordinates correspond to the 2D movement along the track and y is the elevation
  • Save trajectories for offline visualization
  • Update Dolphin Emulator to allow for unix fifo pipe frame dumps
    • Train object detection model to detect obstacles in the road for grand prix races