Car Racing Competition at WCCI2008 - Summary
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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...

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
More information available at http://cig.dei.polimi.it

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Car Racing Competition at WCCI2008 - Summary Presentation Transcript

  • 1. Car racing competition(s): lessons learned and future directions Julian Togelius, Daniele Loiacono, Pier Luca Lanzi
  • 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. 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. 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. 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. 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. 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. 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. 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. 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? • ...it also does not prove that algorithm X is good for any other (car control) tasks • How do we ensure generality?
  • 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?