Research

MachinoAI explainer / AI Agents

Tree of Thoughts: Deliberate Problem Solving with Large Language Models

Tree of Thoughts: Deliberate Problem Solving with Large Language Models explores search and planning over reasoning paths.

Shunyu Yao12 min readResearch
FOUNDATIONALAI AgentsAdvanced

01

Abstract

Search and planning over reasoning paths

02

Introduction

Foundational work on LLM-based agents and Search and planning over reasoning paths.

03

Problem

Addresses how language models can extend beyond single-turn generation through Search and planning over reasoning paths.

04

Methodology

The paper operationalizes Search and planning over reasoning paths through a structured agent mechanism.

Figure notes

Visual evidence

Figure 1
Figure 1

05

Architecture

The system connects an LLM with state, control, tools, memory, environments, interfaces, or other agents.

06

Dataset

Uses task-specific datasets, environments, benchmarks, or interaction traces appropriate to the research question.

07

Training

Uses the training or inference adaptation documented by the primary source; undisclosed details are not inferred.

08

Experiments

Evaluates the proposed mechanism against relevant baselines in the target setting.

09

Baselines

Compares against the underlying model, simpler control strategies, or prior agent mechanisms.

10

Results

Reports evidence for the proposed contribution within its stated benchmark or environment.

11

Conclusion

Contributes a reusable pattern for building or evaluating LLM-based agents.

12

References

Continue reading

Related research

Browse all research