arXiv Artificial Intelligence

Two-Fidelity Best-Action Identification for Stochastic Minimax Tree

1 hour ago 30.09.2026 07:00 👁 1 views
Two-Fidelity Best-Action Identification for Stochastic Minimax Tree

Quick summary

arXiv:2606.01708v2 Announce Type: replace-cross Abstract: We study fixed-confidence best-action identification (BAI) in stochastic minimax trees. This problem is increasingly relevant in modern AI planning, where deep minimax search and Monte Carlo Tree Search (MCTS) with language model long rollouts face a fundamental tradeoff: heuristic evaluations are cheap but biased, while accurate rollouts are reliable but prohibitively expensive. We propose 2FFS, a two-fidelity tree-search algorithm that brings multi-fidelity flat bandit ideas into trees. The algorithm combines minimax-style fast expans

Key takeaways

  • arXiv:2606.01708v2 Announce Type: replace-cross Abstract: We study fixed-confidence best-action identification (BAI) in stochastic minimax trees.
  • This problem is increasingly relevant in modern AI planning, where deep minimax search and Monte Carlo Tree Search (MCTS) with language model long rollouts face a fundamental tradeoff: heuristic evaluations are cheap but biased, while accurate rollouts are reliable but prohibitively expensive.
  • We propose 2FFS, a two-fidelity tree-search algorithm that brings multi-fidelity flat bandit ideas into trees.

Why it matters

The value of this work lies as much in how it was tested as in the claim itself. Sample design, baselines, uncertainty and replication help separate a laboratory result from real-world impact.

Kaynak sitede devamını oku: arXiv Artificial Intelligence ↗