Peter Stone

DM$^2$: Decentralized Multi-Agent Reinforcement Learning for Distribution Matching

2022 · arXiv (Cornell University)

Current approaches to multi-agent cooperation rely heavily on centralized mechanisms or explicit communication protocols to ensure convergence. This paper studies the problem of distributed multi-agent learning without resorting to centralized components or explicit communication. It …

LLM+P: Empowering Large Language Models with Optimal Planning Proficiency

2023 · arXiv (Cornell University)

Large language models (LLMs) have demonstrated remarkable zero-shot generalization abilities: state-of-the-art chatbots can provide plausible answers to many common questions that arise in daily life. However, so far, LLMs cannot reliably solve long-horizon planning problems. …

LaRS: Latent Reasoning Skills for Chain-of-Thought Reasoning

2024

Chain-of-thought (CoT) prompting is a popular in-context learning (ICL) approach for large language models (LLMs), especially when tackling complex reasoning tasks.Traditional ICL approaches construct prompts using examples that contain questions similar to the input question.However, …