Google AI Challenge: Ants

The Google AI Challenge: Ants was an international programming contest held in 2011. My participation focused on two main areas: developing advanced swarm intelligence algorithms and building a scalable infrastructure for distributed testing.

Key Highlights:

• Algorithmic Implementation: Developed a sophisticated bot using Influence Maps for strategic territory control, Minimax with local clustering for tactical combat, and A* for efficient resource collection. These algorithms allowed thousands of ants to operate as a cohesive collective under strict real-time constraints (500ms per turn).
• Distributed Infrastructure: Long before the ubiquity of Docker, I built a custom Master-Worker architecture to run matches across multiple machines. This system enabled rapid iteration by automatically benchmarking new versions of the AI against previous iterations to ensure consistent improvement in ELO rating.
• Performance: Ranked in the Top 100 globally among 7,000+ competitors, demonstrating the effectiveness of the combined algorithmic and infrastructural approach.