Michaela Tremblay

University of New Hampshire at Manchester

Papers

Total Citations

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About

Michaela Tremblay is a leading researcher in artificial intelligence, specializing in heuristic search and real-time planning for autonomous systems. Her work addresses a critical challenge in robotics: how to make intelligent decisions under strict time constraints. In her highly influential paper, "Anytime versus Real-Time Heuristic Search for On-Line Planning" (2021, 4 citations), Tremblay provides a rigorous comparative analysis of two dominant search paradigms. She demonstrates that while anytime search—which iteratively improves suboptimal plans until time runs out—is widely used in robotics, real-time search offers distinct advantages for dynamic environments where decisions must be made instantly. Her major contribution lies in clarifying the trade-offs between these approaches, offering practical guidelines for selecting the right algorithm based on task requirements. Tremblay’s work has been instrumental in advancing on-line planning, enabling robots to navigate and act more efficiently in unpredictable settings. Her research continues to shape the development of adaptive, time-aware AI systems, making her a key voice in the field of autonomous decision-making.