text: Nintendo's Super Smash Bros. Melee fighting game can be emulated on modern hardware allowing us to inspect internal memory states, such as character positions. We created an AI that avoids being hit by training using these internal memory states and outputting controller button presses. After training on a month's worth of Melee matches, our best agent learned to avoid the toughest AI built into the game for a full minute 74.6 of the time.
  @cite_3: An artificial agent is developed that learns to play a diverse range of classic Atari 2600 computer games directly from sensory experience, achieving a performance comparable to that of an expert human player; this work paves the way to building general-purpose learning algorithms that bridge the divide between perception and action.
summary: DeepMind Technologies has successfully learned to play Atari 2600 games using an emulator @cite_3 . DeepMind used a convolutional neural network combined with a Q-learning variant to learn to play games using just the games' pixel output. We plan to build on this success by focusing on a relatively newer game with more complex interactions. Instead of pixels, we look at the game's internal memory, including features such as characters' positions and velocities.