Machine learning and heuristic search

我的研究目的是在机器学习和启发式搜索领域发展科学的理解和改进的算法，并探索这些领域的技术的实际应用。机器学习算法利用训练数据或过去的经验来提高其在特定任务中的性能。在我的研究中，该任务是与单个对手玩扑克，机器学习将被用来识别对手的优势和劣势，并相应地调整其打法，以便最大化地赢得对这个特定对手的胜利。这是非常具有挑战性的，因为学习必须非常快(总共只有100-200手牌将与这个对手对抗)，并且学习算法可用的信息是嘈杂和不完整的。启发式搜索算法是一种在图中两个节点之间寻找最优路径的快速方法。例如，如果图是路线图，则可以使用启发式搜索算法来快速找到从当前位置到特定目的地的最短路径。启发式搜索比标准方法更快，因为它使用了到目标的距离的估计，我的研究调查了各种加快启发式搜索的方法。我正在研究的方法之一是将启发式函数分解为一组较小的启发式函数的和。我的目的是了解什么时候这是可能的，什么时候它比其他方法更好。我还在研究预测给定启发式函数将产生多大加速比的技术。

My research aims to develop scientific understanding and improved algorithms in the areas of machine learning, and heuristic search, and to explore practical applications of techniques in these areas.A machine learning algorithm uses training data, or past experience, to improve its performance at a specific task.  In my research the task is playing poker against a single opponent, and machine learning will be used to identify the opponent's strengths and weaknesses and adapt its play accordingly in order to maximize its winnings against this specific opponent. This is very challenging because learning must be very rapid (only 100-200 hands will be played against this opponent in total), and the information available to the learning algorithm is noisy and incomplete.A heuristic search algorithm is a fast method for finding optimal paths between two nodes in a graph.  For example, if the graph is a road map, a heuristic search algorithm could be used to quickly find the shortest route from your current location to a particular destination.  Heuristic search is faster than standard methods because it uses an estimate of the distance to the goal, called a heuristic function.  My research investigates various ways of speeding up heuristic search.  One of the methods I am investigating is to decompose the heuristic function into the sum of a set of smaller heuristic functions. My aim is to understand when this is possible, and when it is superior to other methods.  I am also investigating techniques for predicting how much speedup will be produced by a given heuristic function.