Agents play a variant of Super Mario, a complete side-scrolling video game with destructible blocks, enemies, fireballs, coins, chasms, platforms, etc. The state space is complicated, but factored in an object-oriented way, which captures many aspects of the real world. Challenges include:
- Path planning: How can Mario navigate around simple obstacles, or through complicated sets of blocks?
- Option learning and execution: Are there reusable sensory-motor primitives which simplify planning? Can these be learned?
- Explore / exploit: Do enemies always behave the same way? Are there stochastic effects of blocks that can be learned?
Environment Properties
- Continuous, single-agent, episodic, RL, uncertainty, complete information.
- Running Instructions
- Download and install Soar.
- Configure environment variables for Soar ($SOAR_HOME)
- Perform the install instructions found at RL-Competition 2009 software. Use the software that is already in the above Infinite Mario download, within the 15-rl-competition-2009 directory
- Configure $COMP_HOME to point to the topmost directory of your local install of the competition software
- Configure $AGENT_HOME to point to the topmost directory of your local install of MarioSoar
- cd $AGENT_HOME
- make clean;make
- Run the agent ./run.bash config/combined.config
- cd to trainer $COMP_HOME/trainers/guiTrainerJava/ for GUI trainer and ./run.bash or $COMP_HOME/trainers/consoleTrainerJava/ for headless trainer
- Pending
- Shiwali Mohan
- Soar 9.3
- Java
- Mohan, S. and Laird, J. E. (2011). An Object-Oriented Approach to Reinforcement Learning in an Action Game. In Proceedings of the Seventh Artificial Intelligence and Interactive Digital Entertainment.
- Mohan, S. and Laird, J. E. (2010). Relational Reinforcement Learning in Infinite Mario (Extended Abstract). In Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence.
- Mohan, S. and Laird, J. (2009). Learning to play Mario (Unrefereed). Center for Cognitive Architecture, University of Michigan, Tech. Rep. CCA-TR-2009-03