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    <guid isPermaLink="false">https://arxiv.org/abs/2501.19278#pheromone-based-learning-of-optimal-reasoning-paths-arxiv-under-review</guid>
    <title>Pheromone-based Learning of Optimal Reasoning Paths</title>
    <link>https://arxiv.org/abs/2501.19278</link>
    <description>We present ACO-ToT, an algorithm that leverages fine-tuned LLM &quot;ants&quot; guided by ant colony optimization to efficiently uncover optimal reasoning paths for complex problems.</description>
    <pubDate>Wed, 01 Jan 2025 00:00:00 GMT</pubDate>
    <author>hello@zhoubrian.com (Brian Zhou)</author>
    <category>Publications</category><category>arXiv (under review)</category>
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    <guid isPermaLink="false">https://arxiv.org/abs/2501.19318#mindstores-memory-informed-neural-decision-synthesis-for-task-oriented-reinforcement-in-embodied-systems-iclr-workshop-on-reasoning-and-planning-for-llms-arxiv-under-review</guid>
    <title>MINDSTORES: Memory-Informed Neural Decision Synthesis for Task-Oriented Reinforcement in Embodied Systems</title>
    <link>https://arxiv.org/abs/2501.19318</link>
    <description>We present MINDSTORES, an experience-augmented planning framework that enables embodied agents to build and leverage mental models through natural interaction, improving zero-shot LLM planning for complex open-world tasks.</description>
    <pubDate>Wed, 01 Jan 2025 00:00:00 GMT</pubDate>
    <author>hello@zhoubrian.com (Brian Zhou)</author>
    <category>Publications</category><category>ICLR Workshop on Reasoning and Planning for LLMs; arXiv (under review)</category>
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