Summary of Synthesizing Interpretable Control Policies Through Large Language Model Guided Search, by Carlo Bosio and Mark W. Mueller
Synthesizing Interpretable Control Policies through Large Language Model Guided Search
by Carlo Bosio, Mark W. Mueller
First submitted to arxiv on: 7 Oct 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Systems and Control (eess.SY)
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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 This paper combines Large Language Models (LLMs), systematic evaluation, and evolutionary algorithms to develop interpretable control policies for complex dynamical systems. By representing control policies as programs in standard languages like Python, the authors enable transparency and interpretability while still leveraging the power of large AI models at the policy design phase. The proposed method is evaluated through simulations and evolves controllers using a pre-trained LLM. Unlike conventional learning-based control techniques, this approach does not rely on black-box neural networks to encode control policies. The authors apply their method to the synthesis of interpretable control policies for the pendulum swing-up and ball in cup tasks, making the code available. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper is about using special kinds of computer models (LLMs) to create new ways to control machines that can do complex things. They want to make these controls easy to understand so people can use them to improve things. To do this, they represent the controls as simple programs that humans can read and change if needed. This way, people can understand how the machines are working and make adjustments based on their own ideas. The authors tested this idea with two specific tasks – making a pendulum swing up and moving a ball into a cup – and shared their code so others can use it. |
