Summary of Eliciting Problem Specifications Via Large Language Models, by Robert E. Wray et al.
Eliciting Problem Specifications via Large Language Models
by Robert E. Wray, James R. Kirk, John E. Laird
First submitted to arxiv on: 20 May 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Computation and Language (cs.CL)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary A novel approach is proposed in this paper to utilize large language models (LLMs) for mapping natural language problem definitions into semi-formal specifications that can be utilized by existing reasoning and learning systems. The design of LLM-enabled cognitive task analyst agents is presented, which produce definitions of problem spaces from tasks specified in natural language. By leveraging LLM prompts derived from AI literature and general problem-solving strategies (Polya’s How to Solve It), a cognitive system can use the problem-space specification to solve multiple instances of problems from a given class using domain-general problem solving strategies like search. This preliminary result suggests the potential for speeding up cognitive systems research by disintermediating problem formulation while retaining core capabilities such as robust inference and online learning. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Large language models can help solve problems! Imagine you have a problem to solve, and you need to explain it in a way that a computer can understand. This paper shows how large language models (LLMs) can be used to translate natural language descriptions of problems into a format that computers can use to try to solve the problem. The authors describe a system that uses LLMs to define problem spaces, which are specifications for solving problems. By using these definitions, computers can apply general problem-solving strategies to solve multiple instances of the same problem. |
Keywords
» Artificial intelligence » Inference » Online learning
