Arriving Intruder

The "arriving intruder" problem focuses on developing strategies for defending a target from a sequence of attackers appearing at unpredictable times and locations. Current research emphasizes optimizing defender resource allocation and movement using techniques like reinforcement learning, priority-based resource allocation, and multi-agent systems, often incorporating computer vision for state estimation in realistic scenarios. This research is significant for improving security in various domains, from protecting critical infrastructure against drone intrusions to enhancing autonomous systems' ability to respond to dynamic threats. The development of robust and efficient defense strategies against unpredictable attackers has broad implications for both theoretical game theory and practical applications in security and robotics.