X and more Parallelism. Integrating LTL-Next into SAT-based Planning with Trajectory Constraints while Allowing for even more Parallelism - Gregor Behnke; Susanne Biundo (Inteligencia Artificial, 2018)
Linear temporal logic (LTL) provides expressive means to specify temporally extended goals as well as preferences. Recent research has focussed on compilation techniques, i.e., methods to alter the domain ensuring that every solution adheres to the temporally extended goals. This requires either new actions or an construction that is exponential in the size of the formula. A translation into boolean satisfiability (SAT) on the other hand requires neither. So far only one such encoding exists, which is based on the parallel $\exists$-step encoding for classical planning. We show a connection between it and recently developed compilation techniques for LTL, which may be exploited in the future. The major drawback of the encoding is that it is limited to LTL without the X operator. We show how to integrate X and describe two new encodings, which allow for more parallelism than the original encoding. An empirical evaluation shows that the new encodings outperform the current state-of-the-art encoding.