Key Responsibilities

  • Applied multi-agent reinforcement learning to develop an improved path-finding system for simulations
  • Designed and tested Unity simulations in C# to enhance AI decision-making and coordination
  • Applied machine learning to train agents for complex tasks and optimize their behavior
  • Collaborated on reports and contributed to academic discussions, enhancing the quality of research outputs

Notable Achievements

  • Improved multi-agent reinforcement learning performance through reward shaping techniques inspired by video game design principles
  • Demonstrated coordinated behavior among multiple agents in Unity simulations, validating reinforcement learning strategies for complex tasks