Car Racing Competition at WCCI2008 - Summary


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Summary of the Car Racing Competition held at the 2008 IEEE World Congress on Computational Intelligence, organized by Daniele Loiacono, Julian Togelius, Pier Luca Lanzi
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Car Racing Competition at WCCI2008 - Summary

  1. 1. Car racing competition(s): lessons learned and future directions Julian Togelius, Daniele Loiacono, Pier Luca Lanzi
  2. 2. Car Racing Competition: 2007, 2008, 2009...? • We want to make this a recurring event, increasing both the quality of submitted controllers and of the competition organization • Last year: used the simplerace game (lightweight Java implementation) • 5 entries for CIG, 12 for CEC
  3. 3. Comparing TORCS to simplerace • More advanced/realistic (e.g. better dynamics and collision handling, gear shifting) • Harder (in a sense) • Completely deterministic (no noise) • Slower. Much slower... • Not completely cross-platform • Not designed for learning algorithms
  4. 4. Not designed for learning algorithms... • Overhead from restarting • Memory leak • Not simple for client to select track • Instant shutdown from excessive car damage • Exploits (degenerate strategies possible) • crossing the start line backwards!
  5. 5. However... • All of the problems (except memory leak) have been solved with client- or server-side patches • Taken together, TORCS is the best alternative we’ve found
  6. 6. The future of the car racing competition • We want to make this a recurring event, continuously improving the quality of both competition and entries • Next iteration confirmed for CIG 2008 • Several questions regarding in which direction to evolve the competition... • we want your input!
  7. 7. The future of the car racing competition • What can we improve? • Measuring learning rather than design • Accessibility and participation • Validity and generality of results • Dissemination
  8. 8. Measuring learning rather than design skills • How do we measure the power of learning algorithms and representations rather than the competitors’ programming skills? • Varying the task (e.g. tracks, cars) between training and scoring • Automatic, track-specific learning phase after submission • Is this important?
  9. 9. Accessibility and participation • Last year we had much higher participation second time around (same software) • How can we make it easier to participate? • Interfaces in more languages? (which?) • More example trainers / controllers? • Should we reach out to other communities? (classical RL people, game developers etc.)
  10. 10. Validity and generality (what can we learn?) • That a controller based on algorithm X wins, does not prove that algorithm X is better than others for car racing... • How do we improve the validity of the competition results? • also does not prove that algorithm X is good for any other (car control) tasks • How do we ensure generality?
  11. 11. Dissemination • More people will submit better controllers if they can get a publication out of it • Last year’s competitions became a 37-page GPEM paper... • Is there a better publication format? Special issues? Workshop proceedings?