Gridworld Search and Rescue: A Project Framework for a Course in Artificial Intelligence
Eric R. Eaton · 2008
This paper describes the Gridworld Search and Rescue sim-ulator: freely available educational software that allows stu-dents to develop an intelligent agent for a search and rescue application in a partially observable gridworld. It permits stu-dents to focus on high-level AI issues for solving the problem rather than low-level robotic navigation. The complexity of the search and rescue problem supports a wide variety of solu-tions and AI techniques, including search, logical reasoning, planning, and machine learning, while the high-level GSAR simulator makes the complex problem manageable. The sim-ulator represents a 2D disaster-stricken building for multiple rescue agents to explore and rescue autonomous injured vic-tims. It was successfully used as the semester project for CMSC 471 (Artificial Intelligence) in Fall 2007 at UMBC.