Real-World Planning with PDDL+ and Beyond
This addresses the problem of limited planning tools for hybrid systems in real-world AI applications, though it appears incremental as it builds on existing PDDL+ standards.
The paper tackles the slow adoption of PDDL+ for real-world AI planning due to limited software and rigid planners by introducing Nyx, a novel planner designed for lightness, simplicity, and adaptability, enabling customization beyond PDDL+ to facilitate broader use in various applications.
Real-world applications of AI Planning often require a highly expressive modeling language to accurately capture important intricacies of target systems. Hybrid systems are ubiquitous in the real-world, and PDDL+ is the standardized modeling language for capturing such systems as planning domains. PDDL+ enables accurate encoding of mixed discrete-continuous system dynamics, exogenous activity, and many other interesting features exhibited in realistic scenarios. However, the uptake in usage of PDDL+ has been slow and apprehensive, largely due to a general shortage of PDDL+ planning software, and rigid limitations of the few existing planners. To overcome this chasm, we present Nyx, a novel PDDL+ planner built to emphasize lightness, simplicity, and, most importantly, adaptability. The planner is designed to be effortlessly customizable to expand its capabilities well beyond the scope of PDDL+. As a result, Nyx can be tailored to virtually any potential real-world application requiring some form of AI Planning, paving the way for wider adoption of planning methods for solving real-world problems.