MyPDDL: Tools for efficiently creating PDDL domains and problems
This provides incremental support for knowledge engineers in AI planning by improving efficiency and error detection in PDDL development.
The paper tackled the problem of time-consuming and error-prone creation of PDDL domains and problems by presenting myPDDL, a modular toolkit, which in user tests showed that syntax highlighting helped detect 36% more errors and a type diagram generator reduced task time by 48%.
The Planning Domain Definition Language (PDDL) is the state-of-the-art language for specifying planning problems in artificial intelligence research. Writing and maintaining these planning problems, however, can be time-consuming and error prone. To address this issue, we present myPDDL-a modular toolkit for developing and manipulating PDDL domains and problems. To evaluate myPDDL, we compare its features to existing knowledge engineering tools for PDDL. In a user test, we additionally assess two of its modules, namely the syntax highlighting feature and the type diagram generator. The users of syntax highlighting detected 36% more errors than non-users in an erroneous domain file. The average time on task for questions on a PDDL type hierarchy was reduced by 48% when making the type diagram generator available. This implies that myPDDL can support knowledge engineers well in the PDDL design and analysis process.