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Ms. Pac-Man Framework

Using reinforcement learning with relative input to train Ms. Pac-Man

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This Java-application contains all required components to simulate a game of Ms. Pac-Man and let an agent learn intelligent playing behaviour using reinforcement learning and either Q-Learning or SARSA.

The framework was developed by Luuk Bom and Ruud Henken, under supervision of Marco Wiering, Department of Artificial Intelligence, University of Groningen. It formed the basis of a bachelor's thesis titled "Using reinforcement learning with relative input to train Ms. Pac-Man", L.A.M. Bom (2012).

Ms. Pac-Man Framework Web Site


  • (Graphical) simulation of the game Ms. Pac-Man
  • Uses a small number of clever relative inputs to represent the game environment
  • Reinforcement learning with either Q-Learning or SARSA
  • Highly configurable and easy to tweak
  • Results can be exported to .CSV or plotted in graphs
  • Extensive documentation


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User Interface

Java AWT, Java Swing

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