Vision for Decisions: Utilizing Uncertain Real-Time Information and Signaling for Conservation

Recent advances in fields such as computer vision and natural language processing have created new opportunities for developing agents that can automatically interpret their environment. Concurrently, advances in artificial intelligence have made the coordination of many such agents possible. However, there is little work considering both the low-level reasoning that allows agents to interpret their environment, such as deep learning techniques, and the highlevel reasoning that coordinates such agents. By considering both together, we can better handle real-world scenarios. We will describe a real-world deployment of conservation drones to illustrate this point.