AI Agents + Robotics
Hybrid Agentic AI for Autonomous Robots
Designed a hybrid AI architecture integrating reinforcement learning, neural perception, and symbolic reasoning to enable autonomous robotic navigation. Built agents using PyTorch and Unity ML-Agents, modeling reward functions for safe and adaptive decision-making. Implemented real-time perception and evaluated policy stability and convergence across dynamic environments.
PyTorch • Reinforcement Learning • Unity ML-Agents • Computer Vision • Search Algorithms