#symbolic reasoning

Discover a step-by-step guide to building a ReAct agent that integrates Prolog logic with Gemini and LangGraph, enabling advanced reasoning and natural language querying.

AbstRaL uses reinforcement learning to teach LLMs abstract reasoning, significantly improving their robustness and accuracy on varied GSM8K math problems compared to traditional methods.

Polaris-4B and Polaris-7B introduce a novel reinforcement learning recipe that scales reasoning capabilities efficiently, achieving state-of-the-art results on math benchmarks with smaller models.

PoE-World introduces a modular symbolic approach that surpasses traditional reinforcement learning methods in Montezuma’s Revenge with minimal data, enabling efficient planning and strong generalization.