Depth-First Proof-Number Search with Heuristic Edge Cost and Application to Chemical Synthesis Planning
Depth-First Proof-Number Search with Heuristic Edge Cost and Application to Chemical Synthesis Planning
Akihiro Kishimoto,Beat Buesser,Bei Chen,A. Botea
2019 · DBLP: conf/nips/KishimotoBCB19
Neural Information Processing Systems · 引用 55 次
TLDR
It is found that DFPN's strengths, that justify its success in games, have limited value in RA, and that an enhanced MCTS variant by Segler et al. significantly outperforms DFPNs in search time, and a novel approach to combine DFPn with Heuristic Edge Initialization is proposed.