PEA*+IDA*: An Improved Hybrid Memory-Restricted Algorithm

It is well-known that the search algorithms A* and Iterative Deepening (IDA*) can fail to solve state-space tasks optimally due time memory limits. The former typically fails in memory-restricted scenarios latter time-restricted scenarios. Therefore, several were proposed using less than IDA*, such as A*+IDA*, a hybrid algorithm combines IDA*. In this paper, we present Partial Expansion (PEA*) This new has two phases, same structure A*+IDA* algorithm. first phase of PEA*+IDA* runs PEA* until it reaches limit, second IDA* without duplicate detection on each node PEA*'s Open. First, model shows how perform better although pure usually makes more expansions A*. Later, an experimental evaluation three limits show that, compared classical planning domains, higher coverage expands fewer nodes. Finally, experimentally analyze both having F-limits priority-queue composition given by have considerable impact performance algorithms.