  With the alarming rise in active shooter incidents (ASIs) in the United
States, enhancing public safety through building design has become a pressing
need. This study proposes a reinforcement learning-based simulation approach
addressing gaps in existing research that has neglected the dynamic behaviours
of shooters. We developed an autonomous agent to simulate an active shooter
within a realistic office environment, aiming to offer insights into the
interactions between building design parameters and ASI outcomes. A case study
is conducted to quantitatively investigate the impact of building exit numbers
(total count of accessible exits) and configuration (arrangement of which exits
are available or not) on evacuation and harm rates. Findings demonstrate that
greater exit availability significantly improves evacuation outcomes and
reduces harm. Exits nearer to the shooter's initial position hold greater
importance for accessibility than those farther away. By encompassing dynamic
shooter behaviours, this study offers preliminary insights into effective
building safety design against evolving threats.
