The Multi-Agent Autonomous Waste Collection System is a research-driven platform that employs multi-agent reinforcement learning to train individual waste-collecting robots to collaborate on route planning. Agents learn to avoid redundant coverage, minimize travel distance, and respond to dynamic waste generation patterns. Built in Python, the system integrates a simulation environment for testing and refining policies before real-world deployment. Users can configure map layouts, waste drop-off points, agent sensors, and reward structures to tailor behavior to specific urban areas or operational constraints.

Symbotic is an advanced AI Agent designed to enhance warehouse automation. By utilizing cutting-edge robotics and AI solutions, it optimizes the flow of goods and inventory within warehouses. The system employs computer vision and machine learning algorithms to facilitate fast and accurate handling of inventory, reducing operational costs and improving efficiency. Its capabilities include autonomous movement of goods, real-time inventory tracking, and data analytics, all aimed at transforming traditional warehouse operations into highly efficient automated systems.