LLM增强的RL:实验表明LLM能够利用自然语言信息处理TSC任务。可将LLM整合到基于RL的TSC任务中,如特征工程、奖励工程。 多路口TSC任务:本文未考虑多智能体相互作用,可探索多路口协作、Agent通信以及其他Agent的行为预测。 基于LLM-Agent的TSC任务:实验揭示了LLM的局限性,即其缺乏TSC任务的专业知识。可整合交通管理知识、...
最近LLM-based Agent成为了LLM一个重要的应用方向,本文是LLM在交通信号控制任务中的应用。 题目:Large Language Models as Traffic Signal Control Agents: Capacity and Opportunity 作者:Siqi Lai, Zhao Xu, Weijia Zhang, Hao Liu, Hui Xiong 机构:香港科技大学(广州) 网址:arxiv.org/pdf/2312.1604 摘要 现存方...
实验是基于九个现实世界和合成数据集进行的,实验展示了LLMLight相对于九个基于交通和基于RL的基线系统的显著效果、泛化能力和可解释性。 TSC的Agent框架如下图所示。 The workflow of LLMLight. 具体而言,将交通信号控制(TSC)视为一个部分可观测的马尔可夫游戏,游戏中的每个agent都装备了一个LLM,管理一个交叉路口的...
This repository contains the code for the paper“iLLM-TSC: Integration reinforcement learning and large language model for traffic signal control policy improvement” - 修改RL wrapper · Traffic-Alpha/iLLM-TSC@f5bbdb9
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1. Title: Attention, Compilation, and Solver-based Symbolic Analysis are All You Need Brief Introduction: 本文提出了一种基于大型语言模型(LLMs)的Java-to-Python(J2P)和Python-to-Java(P2J)代码翻译方法,以及相应的工具CoTran。该方法利用LLMs的注意机制、编译和基于符号执行的测试生成来进行输入和输出程序...
PlanAgent is the first closed-loop mid-to-mid(use bev, no raw sensor) autonomous driving planning agent system based on a Multi-modal Large Language Model. PlanAgent是第一个基于多模态大语言模型的闭环中到中(使用bev,没有原始传感器)自动驾驶规划代理系统。
This approach enhances the TSC system’s adaptability to real-world conditions and improves the overall stability of the framework. Details regarding the RL agent and LLM agent components are provided in the following sections.Large Language Model Guided Reinforcement Learning Based Six-Degree-of-...
iLLM-TSC's powerful capabilities Case3.mp4 Info We propose a framework that utilizes LLM to support RL models. This framework refines RL decisions based on real-world contexts and provides reasonable actions when RL agents make erroneous decisions. ...
● Observability: To reduce reliance on any single inference engine, we have implemented a Go-based reverse proxy that directly collects and computes instance-level performance metrics in real time, such as TTFT, TPOT, instance load, and cache status. ● Hierarchical Scheduling System: Our system...