Trial by fire: understanding the design requirements for agents in complex environments

TLDR

Phoenix is a real‑time adaptive planner for forest fires that also serves as a search for functional relationships between agent design, behavior, and environment, exemplifying a methodology focused on complex, dynamic settings and fully autonomous agents. The study empirically investigates how environmental constraints shape intelligent agent design within Phoenix, while outlining its methodology, architecture, and behavior. The authors employ the Phoenix system—a real‑time adaptive planner—to empirically test how environmental constraints influence agent design.

Abstract

Phoenix is a real-time, adaptive planner that manages forest fires in a simulated environment. Alternatively, Phoenix is a search for functional relationships between the designs of agents, their behaviors, and the environments in which they work. In fact, both characterizations are appropriate and together exemplify a research methodology that emphasizes complex, dynamic environments and complete, autonomous agents. Within the Phoenix system, we empirically explore the constraints the environment places on the design of intelligent agents. This article describes the underlying methodology and illustrates the architecture and behavior of Phoenix agents.