Extending C+ with Composite Actions for Robotic Task Planning

摘要

This paper extends action language C+ by introducing composite actions as sequential execution of other actions, leading to a more intuitive and flexible way to represent action domains, better exploit a general-purpose formalization, and improve the reasoning efficiency for large domains. Our experiments show that the composite actions can be seen as a method of knowledge acquisition for intelligent robots.