This paper describes the Gridworld Search and Rescue simulator: freely available educational software that allows students to develop an intelligent agent for a search and rescue application in a partially observable gridworld. It permits students 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 solutions and AI techniques, including search, logical reasoning, planning, and machine learning, while the high-level GSAR simulator makes the complex problem manageable. The simulator represents a 2D disaster-stricken building for multiple rescue agents to explore and rescue autonomous injured victims. It was successfully used as the semester project for CMSC 471 (Artificial Intelligence) in Fall 2007 at UMBC.
Subjects: 1. Applications; 1.3 Computer-Aided Education
Submitted: May 5, 2008