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.

Ecorithms offers AI-powered waste management solutions like WasteAID to refine route audits, detect overflow, and ensure SB-1383 compliance. Their tools streamline waste management protocols for cities and haulers, providing real-time data and insights to reduce contamination and improve recycling practices. Users can manage, monitor, and optimize waste operations efficiently through their intuitive platform.