GePA*SE: Generalized Edge-Based Parallel A* for Slow Evaluations

Parallel search algorithms have been shown to improve planning speed by harnessing the multithreading capability of modern processors. One such algorithm PASE achieves this by parallelizing state expansions, whereas another algorithm ePASE achieves this by effectively parallelizing edge evaluations. ePASE targets domains in which the action space comprises actions with expensive but similar evaluation times. However, in a number of robotics domains, the action space is heterogenous in the computational effort required to evaluate the cost of an action and its outcome. Motivated by this, we introduce GePASE: Generalized Edge-based Parallel A* for Slow Evaluations, which generalizes the key ideas of PASE and ePASE i.e. parallelization of state expansions and edge evaluations respectively. This extends its applicability to domains that have actions requiring varying computational effort to evaluate them. The open-source code for GePA*SE along with the baselines is available here: https://github.com/shohinm/parallel_search