Pushing the Boundaries of AI Planning

该项目的目标是开发可用于修改人工智能规划算法的规划者通用化技术，以消除人工智能规划经典方法中的一些限制性假设，例如：关于行动和对象以及规划环境、静态规划环境、瞬时行动、离散时间、决定论、黑白解决方案标准的完美知识。该项目的一个起点将是PI在一种方法上的初步结果，该方法“不确定”前向链规划者。该项目将使用理论和经验技术，探索系统地推广规划算法的方法，以处理不确定性、具有概率影响的行动和时间问题。该项目的成果将提供必要的理论和实验基础，使人工智能规划能够更好地满足制造规划和船舶运动规划等现实世界规划应用的需求。本项目中开发的算法的实现将作为开放源码软件提供。

This project has the goal of developing planner-generalization techniques that can be used to modify AI planning algorithms to remove some of the restrictive assumptions found in classical approaches to AI planning, such as: perfect knowledge about actions and objects and history of the planning environment, static planning environment, instantaneous actions, discrete time, determinism, black-and-white solution criteria. A starting point for the project will be the PI's preliminary results on a method to "non-determinize" forward-chaining planners. Using both theoretical and empirical techniques, the project will explore ways to systematically generalize planning algorithms to deal with nondeterminism, actions with probabilistic effects, and temporal issues. Results of the project will provide theoretical and experimental underpinnings necessary to enable AI planning to better address the needs of real-world planning applications such as manufacturing planning and ship movement planning. It is intended that implementations of algorithms developed in this project will be made available as open-source software.