论文标题
学习如何解决泡泡球
Learning How to Solve Bubble Ball
论文作者
论文摘要
“ Bubble Ball”是一款建立在2D物理引擎上的游戏，其中有限的对象可以修改类似气泡的球的运动。目的是选择对象的集合和初始配置，以使球达到目标标志。障碍物，摩擦，接触力和组合对象选择的存在使游戏难以解决。在本文中，我们提出了一个解决气泡球的分层预测框架。几何，运动学和动态模型在层次结构的不同级别上使用。在游戏的每个级别上，在失败迭代期间收集的数据都用于在所有层次结构级别上更新模型，并收集到游戏的可行解决方案。所提出的方法在合理数量的试验中成功解决了大量的气泡球水平。该提出的框架也可用于解决其他基于物理的游戏，尤其是在人类演示的培训数据有限的情况下。
"Bubble Ball" is a game built on a 2D physics engine, where a finite set of objects can modify the motion of a bubble-like ball. The objective is to choose the set and the initial configuration of the objects, in order to get the ball to reach a target flag. The presence of obstacles, friction, contact forces and combinatorial object choices make the game hard to solve. In this paper, we propose a hierarchical predictive framework which solves Bubble Ball. Geometric, kinematic and dynamic models are used at different levels of the hierarchy. At each level of the game, data collected during failed iterations are used to update models at all hierarchical level and converge to a feasible solution to the game. The proposed approach successfully solves a large set of Bubble Ball levels within reasonable number of trials. This proposed framework can also be used to solve other physics-based games, especially with limited training data from human demonstrations.
