Paper summary: Probabilistic planning for continuous dynamic systems under bounded risk

Abstract

This paper presents a model-based planner called the Probabilistic Sulu Planner or the p-Sulu Planner, which controls stochastic systems in a goal directed manner within user-specified risk bounds. We first develop a new plan representation called a chance-constrained qualitative state plan (CCQSP), through which users can specify the desired evolution of the plant state as well as the acceptable level of risk. We then develop the p-Sulu Planner, which can tractably solve a CCQSP planning problem. Copyright © 2013, Association for the Advancement of Artificial Intelligence. All rights reserved.