Graph-of-Thoughts (GoT) Algorithm
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A Graph-of-Thoughts (GoT) Algorithm is an LLM reasoning algorithm that models the reasoning process of large language models as an arbitrary graph structure (rather than a linear chain or tree).
- Context:
- It can provide more flexibility in combining and transforming reasoning paths (more than Chain of Thought or Tree of Thoughts).
- It can present an innovation is representing inferences as a graph rather than a rigid structure.
- It can present a graph model that allows feedback loops, merging chains of thoughts, and other operations not possible in Tree of Thoughts.
- It can (typically) have two main components:
- a Graph of Operations (GoO): A static, preset graph defined by a HUMAN EXPERT that specifies the high-level reasoning steps and transformations required to solve a particular task.
- a Graph Reasoning State (GRS): A dynamic structure that stores the execution details - the history of thoughts generated and their states as reasoning proceeds along the GoO graph.
- …
- A controller module manages execution of the operations laid out in the GoO, coordinating the overall reasoning process. Other modules like prompters and parsers interface with the LLM at each step.
- …
- See: Tree of Thoughts.
References
2023
- code_your_own_AI. (2023). “Graph-of-Thoughts (GoT) for AI reasoning Agents". YouTube vlog post
- SUMMARY:
- Here is a brief summary of how the Graph of Thoughts (GoT) framework works based on the presentation and paper:
- GoT consists of several interacting modules - a Prompter, Parser, Scorer, and Controller.
- The Prompter prepares prompt messages for the LLM. The Parser extracts information from the LLM's responses. The Scorer verifies and evaluates the LLM's replies.
- The key innovation is the Controller, which coordinates the overall reasoning process. It contains two key components:
- Graph of Operations (GoO): A static, preset graph defined by a HUMAN EXPERT that specifies the high-level reasoning steps and transformations required to solve a particular task.
- Graph Reasoning State (GRS): A dynamic structure that stores the execution details - the history of thoughts generated and their states as reasoning proceeds along the GoO graph.
- The Controller manages the progression of reasoning by executing operations in the GoO graph. The GRS tracks changing parameters as this execution proceeds.
- The GoO provides an abstract reasoning plan in the form of a graph, while the GRS registers the concrete execution details. Their interaction enables structured yet flexible reasoning that moves beyond linear chains.
- So, in summary, the Controller drives the reasoning process based on a human-defined GoO graph, with the GRS tracking execution state. The modular architecture coordinates the LLM's inference generation in an interpretable graph framework.
- SUMMARY:
2023
- (Besta et al., 2023) ⇒ Maciej Besta, Nils Blach, ..., Piotr Nyczyk, and Torsten Hoefler. (2023). “Graph of Thoughts: Solving Elaborate Problems with Large Language Models.” In: arXiv preprint arXiv:2308.09687. doi:10.48550/arXiv.2308.09687