Action-Gradient Monte Carlo Tree Search for Non-Parametric Continuous (PO)MDPs

In three linesAction-Gradient MCTS (AGMCTS) combines global tree search with local gradient-based action refinement for online planning in continuous spaces. Three theoretical contributions: action score gradient theorem, Multiple Importance Sampling Tree for sample reuse, tractable gradients via Area Formula. Outperforms state-of-the-art sample-based solvers on continuous MDP/POMDP benchmarks.

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