CASP has a rich research tradition of 70 years . Until 2017, most systems have relied on hand-coded expert systems or data-mining approaches . The more recent introduction of deep neural networks, and RL-inspired search such as MCTS has led to a qualitative step forward, in particular in how reactions are predicted, as well as how potential steps are prioritized during the search . When combined with conditions and sophisticated forward reaction prediction, these algorithms can also be coupled with robotic synthesis . Early ML-based approaches focused on combining graph-based reaction modeling with ML . Recently, purely seq2seq-approaches have also been presented . Several open source implementations are available .