Intelligent Agent Learning

Developed a sophisticated multi-agent reinforcement learning system where AI players autonomously learn optimal soccer strategies through continuous self-play and neural network optimization. 🧠⚽

Research Publications

Successfully published research findings demonstrating novel approaches to cooperative multi-agent learning in competitive environments, with applications extending beyond gaming into robotics and automation. 📊🔬

Game Integration

Adapted the trained models for implementation in existing mobile soccer games, enhancing NPC behavior with human-like decision making and strategic play that scales with player skill level. 📱🎮

Advanced Technology Stack

Built with Unity ML-Agents and TensorFlow for robust machine learning capabilities, implemented in C# and Python. The system leverages deep neural networks for decision making, perception, and cooperative behavior emergence among competing agents. 💻🚀