Tree of Thoughts: Deliberate Problem Solving with Large Language Models
Large language models (LLMs) are becoming increasingly powerful, capable of performing a wide range of tasks. However, they still struggle with tasks that require exploration, strategic planning, or where initial decisions play a critical role. To address this challenge, researchers have introduced a new framework called Tree of Thoughts (ToT) . How ToT Works ToT allows LLMs to perform deliberate decision-making by considering multiple reasoning paths and evaluating choices before selecting the next course of action. It also enables them to look ahead or backtrack when necessary to make informed decisions. Here's a breakdown of how ToT works: Tree Structure: ToT represents the problem-solving process as a tree. Each node in the tree represents a partial solution, and the branches represent different paths that can be taken to reach the final solution. Thought Decomposition: The problem-solving process is broken down into smaller steps called "thoughts." A thought can ...