Software Architecture for Next-Generation AI Planning Systems

TL;DR

This paper proposes a service-oriented architecture for AI planning systems, enhancing usability, interoperability, and reusability, demonstrated through a prototype that offers rapid prototyping and flexible system composition.

Contribution

It introduces a novel service-oriented architecture for AI planning, integrating software design principles to improve system usability and flexibility.

Findings

Prototype demonstrates rapid prototyping capabilities

Architecture improves system flexibility and reusability

Qualitative advantages over traditional planning tools

Abstract

Artificial Intelligence (AI) planning is a flourishing research and development discipline that provides powerful tools for searching a course of action that achieves some user goal. While these planning tools show excellent performance on benchmark planning problems, they represent challenging software systems when it comes to their use and integration in real-world applications. In fact, even in-depth understanding of their internal mechanisms does not guarantee that one can successfully set up, use and manipulate existing planning tools. We contribute toward alleviating this situation by proposing a service-oriented planning architecture to be at the core of the ability to design, develop and use next-generation AI planning systems. We collect and classify common planning capabilities to form the building blocks of the planning architecture. We incorporate software design principles and patterns into the architecture to allow for usability, interoperability and reusability of the planning capabilities. Our prototype planning system demonstrates the potential of our approach for rapid prototyping and flexibility of system composition. Finally, we provide insight into the qualitative advantages of our approach when compared to a typical planning tool.