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Author

Mayank Kejriwal

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#reinforcement learning Open access Sep 2026

Supplementary material from "Code-driven planning in grid worlds with large language models"

We propose an iterative programmatic planning (IPP) framework that solves grid-based tasks by using large language models (LLMs) to synthesize interpretable, executable programs that act as agent policies mapping environment states to action sequences, rather than relying on traditional search or reinforcement learning...

Ashwath Vaithinathan Aravindan, Zhisheng Tang, Mayank Kejriwal · 0 citations
#reinforcement learning Open access Sep 2026

Supplementary material from "Code-driven planning in grid worlds with large language models"

We propose an iterative programmatic planning (IPP) framework that solves grid-based tasks by using large language models (LLMs) to synthesize interpretable, executable programs that act as agent policies mapping environment states to action sequences, rather than relying on traditional search or reinforcement learning...

Ashwath Vaithinathan Aravindan, Zhisheng Tang, Mayank Kejriwal · 0 citations

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