Mark Boddy

Brown University, University of California, Santa Barbara

Papers

Total Citations

307

H-Index

About

Mark Boddy is a pioneering researcher in artificial intelligence, with a primary focus on automated planning, scheduling, and decision-making under uncertainty. His most influential contribution is the foundational concept of "time-dependent planning," introduced in his highly cited 1989 paper (292 citations). This work addressed the critical challenge of how the time spent planning itself impacts the utility of the resulting solution, a problem central to real-time AI systems. By developing the "expectation-driven" framework, Boddy provided a formal method for balancing deliberation and action, a principle that has profoundly influenced subsequent research in anytime algorithms and resource-bounded reasoning. Beyond this theoretical cornerstone, Boddy has applied his expertise to high-impact, real-world domains. He led a major assessment study for the U.S. Department of Energy (2004), identifying key research opportunities in sensors and automation for industrial energy efficiency, prioritizing areas with the greatest potential for energy savings. This work demonstrates his ability to translate complex AI concepts into practical solutions for national-scale challenges, solidifying his reputation as a researcher who bridges rigorous theory with tangible, societal benefit.