Guided Reasoning: A New Approach to Improving Multi-Agent System Intelligence
Practical Solutions and Value
Guided Reasoning is a system where one agent, called the guide, works with other agents to improve their reasoning. This method includes a coach helping a business unit do a SWOT analysis, a child helping their grandmother solve a crossword problem, and a Socratic dialogue.
AI-AI Guided Reasoning is based on the assumption that AI should give the right answers and explain them. It helps AI systems to honestly explain their answers based on clear thinking and makes it easier for AI systems to give the right replies.
Logikon’s standard way of using Guided Reasoning involves steps such as problem statement presentation, client-agent interaction, and evaluation of arguments. This method helps in dividing the cognitive work and creating a clear structure for the thinking process.
By using the thinking trace, the guide creates an informal argument map that makes different arguments clear and shows how they are connected to the competing answer choices. This helps in evaluating the persuasiveness of claims and checking the plausibility of main claims.
Logikon’s Python program matches each step with a different analyst class, using internal processes to make logical artifacts. The program also utilizes IssueBuilder, ProsConsBuilder, RelevanceNetworkBuilder, and FuzzyArgmapBuilder to describe the main issue, build a list of pros and cons, create a relevance network, and generate a fuzzy argument map, respectively.
For companies looking to evolve with AI, Guided Reasoning offers a new approach to improving multi-agent system intelligence. It helps in identifying automation opportunities, defining KPIs, selecting AI solutions, and implementing AI usage gradually.
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