Understanding the Role of Exploration in Search and Planning

作为一名计算科学的研究人员，我的目标是在解决更复杂的现实世界问题方面取得进展。智能自动化决策需要对应用程序领域进行建模，并处理未来可能的备选方案的潜在巨大空间，有时是离线的，但越来越多地是在实时环境中。我和我的研究小组研究解决难题的高效搜索算法。强大的解决方案技术包括抽象、分而治之的策略，以及多种类型的系统和启发式搜索。虽然我的研究议程涉及到这些方法的许多方面的工作，但目前的提议集中在启发式搜索的探索主题上，这已经成为我最近许多工作的共同主题。

As a researcher in Computing Science, my goal is to make progress towards solving ever more complex real-world problems. Intelligent automated decision-making requires modelling an application domain, and processing a potentially huge space of possible future alternatives, sometimes offline but more and more often in a real-time setting. With my research group I study efficient search algorithms for solving hard problems. Powerful solution techniques include abstraction, divide and conquer strategies, and many types of systematic and heuristic search. While my research agenda involves work on many aspects of these approaches, the current proposal focuses on the topic of exploration in heuristic search, which has emerged as the common theme that drives much of my recent work.