2 papers
cs.AI2025
Improved Monte Carlo Planning via Causal Disentanglement for Structurally-Decomposed Markov Decision Processes
Larkin Liu, Shiqi Liu, Yinruo Hua +1
Markov Decision Processes (MDPs), as a general-purpose framework, often overlook the benefits of incorporating the causal structure of the transition and reward dynamics. For a sub…
cs.AI2025
Mastering Board Games by External and Internal Planning with Language Models
John Schultz, Jakub Adamek, Matej Jusup +13
Advancing planning and reasoning capabilities of Large Language Models (LLMs) is one of the key prerequisites towards unlocking their potential for performing reliably in complex a…