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How did John Mosquera apply trading strategies to win the AWS DeepRacer competition?
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John Mosquera drew inspiration from financial trading strategies to excel in the AWS DeepRacer competition. During the qualifying rounds, he adopted an ETFs-type strategy, emphasizing steady growth and risk management. This approach involved crafting a reward function that balanced speed and stability, avoiding penalties while ensuring consistent improvement. In the final round, he shifted to a high-frequency trading (HFs)-inspired strategy, leveraging refined hyperparameters and an aggressive reward function to maximize performance. By applying these trading-inspired methodologies, he demonstrated his ability to transfer domain-specific knowledge to AI/ML challenges effectively. John Mosquera applied ETFs-type and high-frequency trading (HFs)-inspired strategies to win the AWS DeepRacer competition. His reward function designs reflected these approaches, ensuring consistent improvement in qualifying rounds and peak performance in the finals.