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What Kauã demonstrated

Built a DeepRacer reward function end to end and validated it with structured experiments. The final design used track-width-normalized center distance, a steering-aware speed term, and a floored on-track reward, then the student tested variants, measured noise, and correctly diagnosed an unconditional speed bonus as the exploit. They also explained why the function generalized poorly when a finish bonus was tuned to the practice circuit’s step count and proposed a concrete fix.

  • Leakage-Free Reward Design
  • Honest Measurement and Noise Awareness
  • Reward-Hack Diagnosis
  • Generalization Reasoning Across Tracks

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