蒙特卡洛树搜索 在实际对弈中,AlphaGo通过策略⽹络和价值⽹络,配合蒙特卡洛树搜索(Monte Carlo Tree Search,MCTS)来选择棋步。策略⽹络⽤于缩⼩搜索空间,给出可能的好棋步,⽽价值⽹络⽤于评估在各种棋步后的棋局状态。这样,AlphaGo能够平衡探索和利⽤,选择最有可能赢得棋局的棋步。 通过这些⽅法,A...
在实际对弈中,AlphaGo通过策略⽹络和价值⽹络,配合蒙特卡洛树搜索(Monte Carlo Tree Search,MCTS)来选择棋步。策略⽹络⽤于缩⼩搜索空间,给出可能的好棋步,⽽价值⽹络⽤于评估在各种棋步后的棋局状态。这样,AlphaGo能够平衡探索和利⽤,选择最有可能赢得棋局的棋步。 通过这些⽅法,AlphaGo能够在围棋...
在实际对弈中,AlphaGo通过策略⽹络和价值⽹络,配合蒙特卡洛树搜索(Monte Carlo Tree Search,MCTS)来选择棋步。策略⽹络⽤于缩⼩搜索空间,给出可能的好棋步,⽽价值⽹络⽤于评估在各种棋步后的棋局状态。这样,AlphaGo能够平衡探索和利⽤,选择最有可能赢得棋局的棋步。 通过这些⽅法,AlphaGo能够在围棋...
【要点】:论文提出Marco-o1模型,旨在通过Chain-of-Thought fine-tuning、Monte Carlo Tree Search等创新技术,解决开放域问题,并探讨模型在无明确标准和难以量化回报的环境中的泛化能力。 【方法】:Marco-o1模型采用CoT fine-tuning和MCTS等先进技术,结合反思机制和创新推理策略,以适应复杂现实世界问题的解决。 【实验】...
At its core, PromptAgent views prompt optimization as a strategic planning problem and employs a principled planning algorithm, rooted in Monte Carlo tree search, to strategically navigate the expert-level prompt space. Inspired by human-like trial-and-error...
- [Prompt-Based Monte-Carlo Tree Search for Goal-Oriented Dialogue Policy Planning](https://arxiv.org/abs/2305.13660) (May 2023) - [Mitigating Language Model Hallucination with Interactive Question-Knowledge Alignment](https://arxiv.org/abs/2305.13669) (May 2023) - [Making Language Models Be...
(GPT-4.5, GPT-4o) as both task models and prompt optimizers within a Monte Carlo Tree Search (MCTS) framework (Wang et al., 2024b). This setup allows us to examine both task performance and prompt optimization quality under a consistent setting. Our findings are organized around the ...
where fnon−prompt is estimated as a function of pT with a data-driven method, which is based on the construction of data samples with different abundances of prompt and non-prompt candidates. A set of raw yields Yi (index i refers to a given selection on the BDT scores) can be obtai...
Figure 1: Summary of our main results, where LRMs and LLMs are used as either the task model (Mtask) or the optimizer (Mopt) in prompt optimization, and we observed a strong advantage of LRMs over LLMs.图 1:我们主要结果的总结,其中在提示优化中,LRM 和 LLM 被用作任务模型(Mtask)或...