Spatial-Temporal Interplay in Human Mobility: A Hierarchical Reinforcement Learning Approach with Hypergraph Representation

no code implementations • 25 Dec 2023 • Zhaofan Zhang, Yanan Xiao, Lu Jiang, Dingqi Yang, Minghao Yin, Pengyang Wang

In the realm of human mobility, the decision-making process for selecting the next-visit location is intricately influenced by a trade-off between spatial and temporal constraints, which are reflective of individual needs and preferences.

Decision Making Hierarchical Reinforcement Learning +1

Streaming Traffic Flow Prediction Based on Continuous Reinforcement Learning

no code implementations • 24 Dec 2022 • Yanan Xiao, Minyu Liu, Zichen Zhang, Lu Jiang, Minghao Yin, Jianan Wang

We propose to formulate the problem as a continuous reinforcement learning task, where the agent is the next flow value predictor, the action is the next time-series flow value in the sensor, and the environment state is a dynamically fused representation of the sensor and transportation network.

reinforcement-learning Reinforcement Learning (RL) +2