Two Semantics for Step-Parallel Planning: Which One to Choose?

Parallel planning is a paradigm that provides interesting efficiency improvements in the field of classical AI planning and it is one of the key components of successful SAT-based planers. Popularized by the Graphplan algorithm, it provides more structure information about the plan for a plan executor when compared to the traditional sequential plan, which is one of the crucial facts of its usability in real-life scenarios and applications. Our latest research shows that different semantics can be used for parallel planning, while deciding which semantic to use for given application can have significant influence on both practical planning domain modeling and also on the computational efficiency of searching for a plan.