David Bond

University of New Hampshire at Manchester

Papers

Total Citations

H-Index

About

David Bond is a leading researcher in artificial intelligence, specializing in real-time search and decision-making in dynamic environments. His work addresses critical challenges in robotics and video games, where algorithms must return immediate actions within strict time constraints while adapting to changing conditions. Bond’s most influential paper, "Real-Time Search in Dynamic Worlds" (2010, 21 citations), introduced novel algorithms that extend real-time search frameworks—like LSS-LRTA*—to handle fluctuating edge costs before a goal is reached. This contribution is foundational for autonomous agents operating in unpredictable settings, such as rescue robots navigating collapsing structures or game characters reacting to player actions. Beyond this, Bond has advanced heuristic search methods that balance optimality with computational speed, earning recognition for bridging theoretical rigor and practical deployment. His work has been cited by researchers in AI planning, robotics, and interactive entertainment, underscoring its cross-disciplinary impact. Bond continues to push boundaries in adaptive real-time systems, making him a key figure for students and engineers seeking robust solutions for dynamic, time-sensitive problems.