Summary of Agentmove: a Large Language Model Based Agentic Framework For Zero-shot Next Location Prediction, by Jie Feng et al.
AgentMove: A Large Language Model based Agentic Framework for Zero-shot Next Location Prediction
by Jie Feng, Yuwei Du, Jie Zhao, Yong Li
First submitted to arxiv on: 26 Aug 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Artificial Intelligence (cs.AI); Computation and Language (cs.CL); Information Retrieval (cs.IR)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper introduces AgentMove, a systematic framework for generalized next location prediction. It addresses the limitations of existing deep learning methods and large language models (LLMs) in this task by decomposing the mobility prediction task into three specific modules: spatial-temporal memory for individual mobility pattern mining, world knowledge generator for modeling urban structure and collective knowledge extractor for capturing shared patterns among populations. The framework combines the results of these modules and conducts a reasoning step to generate final predictions. Experimental results show that AgentMove surpasses leading baselines by 3.33% to 8.57% across eight out of twelve metrics, with robust predictions using various LLMs as base models and reduced geographical bias across cities. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary AgentMove is a new way to predict where people will go next. Right now, computers aren’t very good at this task because they don’t understand how people move around in the world. A team of researchers created AgentMove to solve this problem. They broke down the prediction task into three parts: remembering what an individual person likes to do, understanding urban structures and collective patterns, and combining all that information to make a final prediction. The results show that AgentMove is better than other methods at predicting where people will go next. |
Keywords
» Artificial intelligence » Deep learning
